Nebius — Jobs & Company Profile

Site Reliability Engineer in Hardware Infrastructure

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The team The Hardware Automation team builds the internal platforms and tooling that power how Nebius operates its data center infrastructure at scale. Our mission is to eliminate manual effort, reduce human error, and give every team in the Hardware Infrastructure department real-time visibility and control over the systems they own. We operate as a product engineering team embedded within hardware infrastructure — meaning we don't just write requirements and hand them off. We own the full stack: from requirements gathering with data center operations and hardware engineering, through design and build, all the way to rollout and ongoing reliability. The role Ensure fault-tolerance, scale and uninterrupted operations for our services. Use cutting-edge technology to solve a variety of infrastructure problems. Implement and improve CI/CD processes. We expect you to have: Proficiency in Linux systems, with expertise in Python and Bash scripting for automation. Demonstrated ability to troubleshoot complex system issues, including hardware, software and networking problems. Strong analytical and problem-solving skills, with a focus on optimizing system performance. Working proficiency in English. It would be an added bonus if you had: Desire to be involved in backend development. Experience designing, developing and running high-load distributed systems. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Technical Program Manager - New Data Center Launches

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role As a Senior Technical Program Manager, you will own the end-to-end delivery of GPU clusters and other critical IT infrastructure components that power next-generation AI workloads. In this high-impact role, you’ll coordinate engineering, networking, construction, and operations teams to deliver GPU clusters and critical IT infrastructure at hyperscale. You’ll work closely with infrastructure leadership to define strategy, manage risk, and ensure on-time, high-quality launches.You’ll play a key role in scaling our global infrastructure footprint across the EU markets. Travel: This position may require on-site presence at data centers during key deployment phases. Your responsibilities will include: Lead end-to-end delivery of new data center programs, from design through handover to operations. Define and manage scope, schedule, and risks, maintaining focus on critical paths and proactive issue resolution. Translate business and technical requirements into actionable project plans and measurable deliverables. Oversee vendor and contractor execution, ensuring quality, budget, and schedule. Provide structured program reporting, including dashboards, documentation, and executive updates. We expect you to have: 7+ years of experience in technical program or project management, with direct involvement in large-scale IT infrastructure deployments. Solid technical background in relevant domains, with the ability to engage deeply in technical discussions and challenge solutions where needed. Proven ability to stay focused on critical paths and drive results in fast-paced, changing environments. Communication and stakeholder management skills; able to translate complex topics clearly. Leadership by influence and example in cross-functional or matrixed teams. Proficient with modern project management tools and methodologies (e.g., Jira, Asana, hybrid Agile/Waterfall). It will be an added bonus if you have: Understanding of construction projects structure and key risk factors in facility build-outs. Knowledge of HPC Experience in business processes design or automation tools development. PMP, PRINCE2, or similar industry certifications. #LI-RK1 Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Technical Product Manager - Token Factory

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role We’re building Nebius Token Factory, an AI inference platform for high-performance, cost-efficient workloads at scale, serving both developers and managed enterprise customers. As a Senior/Principal Product Manager, Inference Platform, you’ll join a team of PMs under the Inference Platform lead and own a core platform stream end to end, from strategy and roadmap to launch and adoption. The scope evolves quickly with the market (new models, modalities, hardware and customer needs), with a strong emphasis on scalability and reliability. Your responsibilities will include: Own the roadmap and outcomes for a part of the inference platform, aligning several cross-functional engineering teams across public API, routing, performance, reliability and enterprise enablement features. Work with engineering and research to make inference more scalable, reliable and cost-efficient, and turn that into capabilities customers can depend on. Stay close to customers through research, interviews and hands-on PoCs, especially in managed enterprise. Track the market: open-source models, inference economics, and how businesses actually apply AI. Turn what you see into product bets. We expect you to have: Experience shipping technical platform products, with the seniority to lead work across multiple engineering teams. Real technical depth in how AI inference works, including model serving, distributed systems and production infrastructure. You think problems through yourself rather than relying on engineers to define them. Strong communication and expectations management across engineering, research, sales, support and leadership. You write crisp PRDs, RFCs and release notes. B2B/enterprise experience with technical buyers. Comfort with ambiguity and shifting scope. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Technical Product Manager - AI Compute Platform

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role: Our customers build the frontier of AI on top of Nebius — training state-of-the-art models, running production inference at scale, shipping the research and products that define where the field is going next. We are building the AI cloud that the people building the frontier of AI choose deliberately — not on price, not on raw capacity, but on how it works to use it day to day. To do that, we are growing the AI Compute Platform product team and hiring multiple Technical Product Managers across the full surface of the platform. Your scope will be defined by what you bring. We will match your technical strengths, customer experience, and product instincts to the area of the platform where you can have the most impact. The platform is broad — and at our scale, every slice is mission-critical.If you want to help build the best AI cloud in the world — and you have the technical depth to engage engineering leaders as a peer (not as a translator) and the comfort to talk to customers directly — this team is for you. The platform you'll help build: Hardware platforms & launch — bringing new GPU and CPU platforms (GB300, Vera Rubin, ARM/Grace, future generations) to production with full launch readiness across the stack. Cluster lifecycle & fleet operations — new region launches, 100,000+ GPU cluster bring-up, platform sharding and allocation architecture, release engineering, host-lifecycle automation, operational efficiency. Reliability & Mission Control — autohealing, health checks, SLA, fault-tolerant training, MTTR reduction, customer trust at scale, observability as a product. Customer experience & developer surface — Compute APIs, console, CLI, IMDS and in-VM signals, self-service workflows, notifications, customer-facing observability, unified UX across the product line. GPU & InfiniBand foundational services — drivers, firmware, NCCL, IB/RoCE, NVLink topology, the foundational layer everything else builds on. Managed runtime platforms — Soperator (Slurm-on-Kubernetes) and MK8S (Managed Kubernetes for AI workloads), powering training and inference for frontier labs. Platform integrations & emerging workloads — Token Factory integration, RL and agentic workload infrastructure, capacity sharing, new business surfaces as they emerge. Cross-platform program & delivery — NVIDIA partnership programs, major-maintenance orchestration, cross-stream releases. You will own one of the slices of this platform end-to-end — from strategy and roadmap through delivery, adoption, and measurable outcomes. Your responsibilities will include (regardless of which slice you own): Own end-to-end product responsibility for your area — strategy, roadmap, discovery, delivery, adoption, measurable customer and platform outcomes. Design and own the platform contracts customers depend on — APIs, semantics, system events, customer-facing surfaces, operational behavior — at hyperscaler quality. Drive cross-team execution across platform engineering, networking, storage, Soperator/MK8S, observability, IAM, billing, capacity planning, support, and product design. Turn customer pain into product commitments through structured discovery — interviews, usage analytics, support patterns, incident postmortems. Close the loop so the same class of failure or friction does not recur. Engage engineering as a technical peer — debate API design, reason about system trade-offs, judge the quality of platform internals, and push back when the design is wrong. Define and own success metrics — what you ship is measured by what changed for the customer or the platform, not by the size of the spec. Be the product voice that customer-facing teams (Support, CX, TAMs) escalate to when a system behavior, API contract, or operational pattern needs a product decision, not a workaround. We expect you to have: 6+ years in Product Management, Platform PM, Infrastructure PM, or SRE / Engineering Lead with strong product instincts. Strong technical foundation and cloud-infrastructure depth — comfort reasoning about API semantics, control-plane vs data-plane behavior, system events and lifecycle, multi-tenant operational realities. You can engage engineering leaders as a peer, not as a translator. Experience with cloud, GPU, or HPC infrastructure — either building one or operating one at meaningful scale (thousands of nodes, multi-region, multi-tenant). Track record of shipping technically complex platform products with measurable customer or platform impact — quantitative results, not aspirational bullets. Strong analytical skills: comfort defining and instrumenting product metrics, working with telemetry, building data-informed roadmaps. Experience leading discovery-heavy work — structured customer interviews, usage analytics, support-ticket analysis — and turning insights into shipped product. Strong communication and ability to align engineering, SRE, customer-facing teams, and exec stakeholders. High ownership, bias to ship, comfort with messy operational reality, and the instinct to push back on engineering when the customer experience or platform quality would suffer. It will be an added bonus if you have (these are not all required — different strengths fit different slices of the platform): Customer-facing experience and lived-it perspective: Direct PM experience with frontier AI customers — ML platform teams, MLOps engineers, training and inference at scale. Familiarity with Kubernetes, Slurm, or HPC environments from the user side, and ML training workflows. Hands-on experience with ML training and inference workflows — especially distributed training at scale (multi-node, multi-GPU; comfort with checkpointing, NCCL, fault-tolerant training, debugging large training jobs). Experience as a customer of AI cloud infrastructure at large scale — especially as part of an internal ML platform team that built and operated infrastructure for ML engineers inside your own company. If you have lived through what frustrates customers about clouds, you will know exactly what we are trying to fix. Hardware, GPU, and HPC depth: Direct experience with NVIDIA reference architectures (NVL72, SuperPOD, MGX, DGX) and the NVIDIA stack (drivers, CUDA, NCCL, DCGM). Familiarity with InfiniBand / RoCE fabrics, firmware lifecycle, topology-aware scheduling. Hands-on with GPU clusters or HPC fabrics at thousands-of-nodes scale. Cluster and fleet operations: Background in Kubernetes lifecycle (CAPI, cluster upgrades, node-pool management) or Slurm at scale. Experience launching new cloud regions or data-center bring-ups end-to-end. Background in release engineering, change management, or major-maintenance orchestration in production environments. Customer experience and developer surface: Exposure to console / CLI / API design at hyperscaler quality — AWS, GCP, Azure depth on consistency, versioning, idempotency, error semantics, deprecation policy. Background in observability product — Grafana, Datadog, Honeycomb, New Relic. Knowledge of customer trust artefacts — status pages, RCA workflows, audit logs, SLA reporting, maintenance notifications. Familiarity with developer-experience product patterns — Stripe, Cloudflare, Vercel, Supabase, Render. Reliability and operational outcomes: Background in SRE, reliability engineering, or fault-tolerant systems for paying customers. Familiarity with reliability metrics that matter: Goodput, MFU, MTTR, MTBF. Experience with autohealing systems and graceful failure semantics. Emerging workloads and integrations: Familiarity with RL / agentic / inference workload patterns — vLLM, SGLang, Ray, Token Factory-style serving, sandbox technologies (Firecracker, gVisor, Kata). Experience with multi-product cloud integrations — capacity sharing, billing models, cross-product packaging. Background in pricing strategy for infrastructure products (reserved / on-demand / preemptible tiers, two-part pricing). Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Systems HPC Engineer

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. We are looking for a Senior Systems HPC Engineer to play a key role in building our hyperscaler platform, working across its core components while analyzing and optimizing the performance of large-scale GPU clusters at the intersection of hardware and software. You will operate across the full stack—from hardware and system software to networking (InfiniBand/RoCE), virtualization (KVM/QEMU), and distributed communication layers (e.g., MPI, NCCL). In this role you will Focus on understanding system behavior across multiple layers, identifying performance bottlenecks, and driving improvements that shape how our clusters are built, operated, tuned, and validated. Investigate and troubleshoot performance issues of GPU cluster under real workloads (training and inference) Evaluate and integrate new hardware, system configurations and tuning approaches through software stack Support complex performance-related escalations from internal teams and customers Work closely with infrastructure, software engineering and hardware vendor teams (e.g. NVIDIA, Mellanox, Intel) Contribute to hardware and cluster qualification (acceptance), ensuring systems meet performance expectations We expect you to have: 5+ years of professional experience in system-level software development (focused on performance optimization, low-level programming).  3+ years of hands-on experience with Linux systems (administration, troubleshooting, and performance tuning).  In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems.  Strong proficiency in one or more performance-oriented programming languages (C/C++, Go, Python). We conduct coding interviews as part of the process. #LI-LH2 Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior System Engineer (CloudGate)

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role Our CloudGate team is responsible for the software side of external network connectivity in our Cloud. We're building a traffic delivery system for a variety of scenarios: IPv4 connectivity, Cloud Interconnect, Egress NAT, and a network load balancer. They serve tens of millions of packets per second. We have a control plane microservice architecture with gRPC transport and our own Database as our data warehouse. What we do: Increase service scalability Developing service functionality with support for service endpoints and expansion of health check types Improve the internal architecture, optimizing interaction with related services In this position, your responsibility will be to: Developing a data plane for Nebius Cloud network services Improve service performance and reliability Automate complex cross-service interaction scenarios Perform load testing for services We expect you to have: Capable of writing reliable, high-performance code Proficient in C and ready to learn Go/C++ Familiar with routing network traffic It would be an added bonus if you had: Worked with VPP, DPDK, and the Linux kernel network subsystem Well-versed in virtual networks and overlays, SDN, NFV, DPI, network protocols, routing and tunneling, BGP, and MPL We conduct coding interviews as part of the process. #LI-JS1 Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior/Staff Application Security Engineer

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. Application Security The team is responsible for the security of Nebius's main public offerings : Compute, VPC, Managed K8s, Marketplace, Managed Soperator, and others. This includes building out the Secure SDLC, threat modeling, and vulnerability management platforms. The Role We are looking for an Senior/Staff Application Security Engineer who will ensure the security of our software by identifying and mitigating vulnerabilities, implementing best security practices, and collaborating with development teams. The ideal candidate will have a strong background in secure coding, threat modeling and building Secure SDLC. What you will do Build and maintain Application Security Posture Management (ASPM) at the Company scale. Automate and support SAST, SCA tools, etc as part of CI/CD pipelines. Improving SAST, secrets detection rules. Keeping false positive rate low. Identify, analyze, and remediate application security vulnerabilities. Collaborate with development teams to integrate security best practices into the software development lifecycle (SDLC). Develop and maintain secure coding guidelines for development teams. Conduct, run threat modeling and risk assessments for new and existing applications. Provide development teams with instruments that facilitate security-related work like threat modelling, vulnerability detection, etc. Stay updated on the latest security threats, vulnerabilities, and mitigation techniques. Serve as an application security subject matter expert to other teams. What we look for 6+ years of experience in application security. Strong knowledge of common application security risks (e.g. OWASP Top 10) and how to mitigate them. Experience with secure coding practices in languages such as Python, Go, Java, or JavaScript. Proficiency in a common programming language (such as Go or Python) with a willingness to learn Go, if necessary. Hands-on experience with security testing tools (Burp Suite, ZAP, Semgrep, etc.). Understanding of authentication protocols like SAML or OIDC. Experience in conducting threat-modeling sessions. Bonus points Confidence in presenting your ideas and opinions in a manner that can be challenged, while responding well to feedback. Experience in designing, building, and maintaining security automation. Experience in translating compliance and regulation requirements into technical specifications. Experience in exploiting vulnerabilities in web applications, Linux kernels, containers, and networks. Security certifications such as OSCP or OSWE. Hiring process Recruiter's chat (30mins) Live-coding interview (60mins) to asses basic coding skills Security interview (60mins) to asses domain expertise Security System Design interview (90mins) to assess practical experience (Optional) Technical deep dive (90mins) to present a complex and impact project. Final interview to close the hiring process (45mins) #LI-CP1 Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Software Engineer (YDB Team)

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role The YDB Development Team at Nebius is hiring mid- and senior-level software developers with C++ expertise. YDB is an open-source platform with two roles within Nebius: Providing the binary object storage foundation for S3 Object Storage, Shared Filesystems and Network Block Storage Serving as a distributed relational database and message broker for services such as IAM, billing, audit trails and logging We operate YDB clusters in more than 10 regions using HDD and NVMe storage. Individual clusters span tens of thousands of nodes, manage hundreds of petabytes of data and deliver terabytes per second of throughput. Our infrastructure includes x86 and Arm-based systems, including NVIDIA GB300 nodes. What you’ll work on Evolve YDB’s architecture for new hardware, redesigning core components when incremental optimization is insufficient: QLC NVMe drives: increase storage density while controlling RAM/CPU consumption and write amplification Dual 800 Gb/s network adapters: reduce CPU overhead and memory bandwidth consumption to utilize the available NIC bandwidth NVIDIA GB300-based systems: ensure efficient operation on Arm-based hosts and offload storage and networking processing to BlueField DPUs Support high-capacity SMR HDDs by designing data placement, sequential writes, garbage collection and recovery around zoned-write constraints Develop wide erasure-coding schemes to reduce space aplimfication while maintaining durability and availability Reduce recovery and rebalancing times after device outages while limiting the impact on foreground workloads Prevent, detect and recover from silent data corruption across memory, networking and storage Provide the system capabilities and interfaces required by fleet-wide automation so that hundreds of production clusters can be deployed, configured, upgraded, diagnosed and operated consistently We move quickly and focus on delivering practical value. Features and optimizations merged into the production branch are typically deployed within weeks. You’ll see your work solving real problems in live clusters—not waiting years to make an impact. Requirements: 5+ years of professional experience developing high-load systems in C or C++. Candidates with 3+ years will also be considered if their experience includes relevant work on distributed storage systems Experience developing high-performance, low-latency software components Understanding of core dumps, flame graphs and sanitizer-enabled builds Understanding of CPU caches, atomic operations and NUMA architectures Nice to have: Experience designing and developing production-grade distributed storage systems and/or databases Experience with on-disk data structures such as LSM trees and B+ trees, and storage algorithms such as erasure coding and checksumming Understanding of NVMe, conventional HDD and SMR HDD internals Experience with debugging and profiling tools such as perf, VTune, bpftrace and gdb Familiarity with the Linux kernel, SPDK/DPDK, libaio and io_uring Knowledge of IP, TCP, UDP and DNS, and ideally InfiniBand or RoCE/RDMA Experience with Kubernetes and Grafana Experience responding to production incidents Knowledge of availability and durability calculations For Senior candidates, we offer hybrid working or the flexibility to work remotely within EU. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Software Engineer (Agentic Search) – Web Rendering (Chromium)

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The Product In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale. The Role We are looking for a Senior Software Engineer to work on the rendering infrastructure of a novel search engine tailored for agentic AI consumption. In this role, you will focus on loading modern web pages in a browser that we patch and build ourselves, so that content is rendered completely and reliably at a cost that works across billions of pages. You will work inside Chromium to remove what we do not need, make the rest faster and cheaper, and keep our build current as Chromium moves. Your work ensures that high-quality content is consistently available to the indexing and retrieval systems downstream. In this position, your responsibility will be to Change Chromium in its heavy core (Blink, the V8 integration, the compositor, the network service) to cut CPU, memory and startup cost per page Strip Chromium down for agent workloads: skip what nobody needs, such as image and media decoding, web font downloads, and rasterization and GPU work where no one needs pixels, while keeping what page scripts depend on to run correctly (style, layout, animation frames, observers), and work out what breaks, or renders differently, when you do Keep the browser compatible with the web: make sure that what we remove does not change how the sites we load behave or render Profile and tune fleets of browsers: the process model, memory per renderer, startup, isolation and crash handling Build the production system around it: how browsers are launched, pooled, recycled and monitored You may be a good fit if you Have 5+ years of experience building production systems, and are an expert in several of the following areas. Inside the browser Strong C++ in a large, performance-critical codebase, ideally Chromium, Blink or V8, or a comparable browser engine (Rust is a plus) Chromium architecture: the process model, Mojo IPC, the rendering pipeline (DOM, style, layout, paint, compositing), and the network service Building, debugging and shipping custom Chromium builds: the build system, tracing, crash analysis, and maintaining patches across releases Performance and systems Profiling CPU, memory and I/O for browser fleets, with tools such as perf, tracing and flame graphs Linux process isolation and resource management, concurrency, and memory management Have run browsers in production, or built the infrastructure that does, and can describe where the time and memory went Strong candidates may also have experience with Contributions to Chromium, Blink, V8, Firefox, WebKit or another browser engine Building or maintaining a patched browser that you wrote the patches for Browser instrumentation, including the Chrome DevTools Protocol Working familiarity with how modern frontend frameworks render (SSR, CSR, streaming, hydration) Distributed systems, Kubernetes, and Go or Python The kind of problems you will work on Cut the cost of loading a page in half. Where do CPU and memory go, and what would you change in the browser? Turn off the GPU and image decoding for agent workloads. What breaks, and what changes in how pages load and render? A page runs a script that never yields. How do we detect and stop it without help from the page? Chromium ships a new version. How do we bring a large set of patches forward in days, not weeks? Decide when a page is finished, for pages with analytics beacons, long polling and endless scrolling. We conduct coding interviews as part of the process. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Site Reliability Engineer — Token Factory (Inference Platform)

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. Token Factory is a part of Nebius Cloud, one of the world’s largest GPU clouds, running tens of thousands of GPUs. We are building an inference platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to deploy at massive scale. To deliver on that promise, we need an engineer who can make the platform behave flawlessly under extreme load and recover gracefully when the unexpected happens. In this role you will own the reliability, performance, and observability of the entire inference stack. Your day starts with designing and refining telemetry pipelines — metrics, logs, and traces that turn hundreds of terabytes of signal into clear, actionable insight. From there you might tune Kubernetes autoscalers to squeeze more efficiency out of GPUs, craft Terraform modules that bake resilience into every new cluster, or harden our request-routing and retry logic so even transient failures go unnoticed by users. When incidents do arise, you’ll rely on the automation and runbooks you helped create to detect, isolate, and remediate problems in minutes, then drive the post-mortem culture that prevents recurrence. All of this effort points toward a single goal: scaling the platform smoothly while hitting aggressive cost and reliability targets. Success in the role calls for deep fluency with Kubernetes, Prometheus, Grafana, Terraform, and the craft of infrastructure-as-code. You script comfortably in Python or Bash, understand the nuances of alert design and SLOs for high-throughput APIs, and have spent enough time in production to know how distributed back-ends fail in the real world. Experience shepherding GPU-heavy workloads — whether with vLLM, Triton, Ray, or another accelerator stack — will serve you well, as will a background in MLOps or model-hosting platforms. Above all, you care about building self-healing systems, thrive on debugging performance from kernel to application layer, and enjoy collaborating with software engineers to turn reliability into a feature users never have to think about. If the idea of safeguarding the infrastructure that powers tomorrow’s multimodal AI energizes you, we’d love to hear your story. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Site Reliability Engineer (SRE, Compute Node Team)

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The Role We are looking for a Senior Site Reliability Engineer (SRE) to join the Compute Node team at Nebius AI Cloud. The Compute Node team is responsible for building and operating the cluster scheduler and node-level services that run and manage virtual machines across all cloud regions. This role focuses on Linux systems engineering, virtualization and operational reliability. You will work close to the operating system and hypervisor, shaping how reliability and observability are embedded into the Compute platform. Your responsibilities will include: Ensure reliability, availability and performance of compute nodes running VMs Analyze and debug Linux systems across user space and kernel space, understanding capabilities, limitations and trade-offs at each layer Troubleshoot complex production issues involving CPU, memory, NUMA, cgroups and scheduling Work hands-on with virtualization and containerization, primarily using QEMU/KVM and Linux-native technologies Design and evolve observability as a core capability of the node layer: metrics, logs, traces, alerts, SLIs and SLOs Lead incident response, root-cause analysis, and postmortems, driving long-term reliability improvements Collaborate closely with platform, kernel/hypervisor, GPU and infrastructure teams to improve system design and operability We expect you to have: Strong Linux expertise: deep understanding of Linux user space and kernel space knowledge of kernel subsystems (scheduler, memory management, filesystems, cgroups, namespaces) clear understanding of system boundaries and constraints at different layers Virtualization experience: hands-on experience with QEMU/KVM understanding of VM lifecycle, performance characteristics and failure modes Containerization knowledge: practical experience with containers, namespaces and cgroups strong understanding of resource isolation and control Strong debugging skills: ability to reason about complex system failures structured, hypothesis-driven approach to incident analysis SRE mindset: clear understanding of the SRE role in system design and operations experience building and operating observability stacks, not just consuming them ability to turn system behavior into actionable reliability signals Nice to Have / Optional: Experience with Kubernetes internals or node-level components Hands-on experience with low-level Linux debugging tools (e.g. perf, eBPF, ftrace, strace, kernel crash dumps) Familiarity with large-scale compute or bare-metal platforms Contributions to open-source infrastructure or system software Experience debugging hardware and driver-level issues, including GPUs, NVLink, InfiniBand Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Site Reliability Engineer (SRE)

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The Role Your responsibilities will include: Ensure fault-tolerance, scale, and uninterrupted operations for the service. Use cutting-edge cloud technology to solve a variety of infrastructure problems. Implement and improve CI/CD processes. We expect you to have: Solid experience with programming languages (like Go, Python, or C++); Solid understanding of classic algorithms and data structures; Commercial experience with and deep understanding of Unix systems and network technology; Experience with systems for containerization and configuration management (Ansible, Salt, Terraform, Docker, K8s, Helm). It will be an added bonus if you have: Desire to be involved in backend development; Experience designing, developing, and running high-load distributed systems; Commercial experience with a variety of cloud platforms. We conduct coding interviews as part of the process. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Site Reliability Engineer (DevTools)

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The Role We're an SRE team within DevTools, looking for someone ready to help maintain and grow our systems. We run 25k builds a day in TeamCity, store 100 TB of artifacts in Artifactory, and work with a massive monorepo in GitLab — comparable in scale to what you'd find at FAANG companies. We modify GitLab and build our own TeamCity plugins to give users a product that meets their needs. We're also experimenting with AI — we have our own RAG setup and are figuring out how to operate in the age of agents. Our goal: understand users' problems and requests, define metrics that capture the problem, improve those metrics, and verify that the user's problem is actually gone. Your responsibilities will include: Improving services based on user feedback Building fault-tolerant, self-healing architecture Finding ways to speed up our systems and reduce user friction Modifying well-known closed- and open-source solutions Supporting our users We expect you to have: A combination of SRE and SWE experience (for us that's a 50/50 split). Our code is in Java/Kotlin, Go, Python, and Ruby An understanding of what's happening under the hood in Unix-like systems and the JVM A passion for improving the user experience The ability to adapt quickly on the fly in a fast-changing environment It will be an added bonus if you have: Experience in Platform Engineering Experience operating GitLab (or another VCS) and TeamCity (or another CI system) Experience with Spring and operating Java monoliths We conduct coding interviews as part of the process. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Product Designer - Compute, Nebius Console

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. About the role Nebius is building cloud infrastructure and AI platforms used at scale. We are looking for a Senior Product Designer to join the Nebius Console team and lead the design of Compute experiences: complex, high-impact workflows used by technical teams to create, configure, monitor, and manage cloud resources. This role is for a designer who enjoys working with complex systems, understands the value of clear interaction models, and can turn technical depth into intuitive, reliable product experiences. Responsibilities Own end-to-end design for Compute features in Nebius Console, from discovery and problem framing to delivery, launch, and iteration. Design clear, scalable workflows for complex cloud infrastructure scenarios, including resource creation, configuration, management, monitoring, and troubleshooting. Translate business goals, technical constraints, and user needs into coherent user journeys, information architecture, and interaction models. Partner closely with Product Managers, Engineers, Designers, UX Researchers, and other stakeholders throughout the product lifecycle. Explore and validate design hypotheses through user insights, prototypes, product data, and feedback from internal and external users. Clearly present design solutions, trade-offs, and rationale to cross-functional teams. Work closely with engineers during implementation to ensure high-quality execution and consistency. Contribute to the development and maintenance of the design system, improving consistency, usability, and quality across Nebius Console. Collaborate within a strong design team through reviews, critiques, shared patterns, and design system contributions. Required qualifications 6+ years of experience as a Product Designer working on digital products. Strong product thinking and the ability to approach design through connected user scenarios, product goals, and system constraints. Experience designing complex B2B, SaaS, developer tools, infrastructure, or admin products. Ability to balance usability, consistency, technical feasibility, and innovation in complex systems. Strong systems thinking, attention to detail, and ability to work in a structured, systematic way. Strong proficiency in Figma, including complex flows, components, variants, and interactive prototypes. Ability to communicate design decisions clearly and constructively with both product and engineering teams. Nice to have Experience designing cloud consoles, infrastructure platforms, developer tools, or other technically complex products. Familiarity with cloud concepts such as virtual machines, compute resources, networking, storage, quotas, permissions, or monitoring. Experience with UX research, usability testing, customer interviews, or feedback analysis. Ability to communicate effectively with engineers using basic HTML, CSS, and JavaScript terminology. Experience working with design systems at scale. What we offer Competitive salary and a comprehensive benefits package. A clear and meaningful area of ownership within one of the core parts of the cloud platform. Opportunities for professional growth as the product, design team, and platform scale. Flexible work arrangements, with hybrid and remote options depending on location A collaborative, product-focused environment with close design–engineering partnership. A strong design team with space for thoughtful critique, shared standards, and high-quality product work. If you enjoy designing complex products, working closely with engineers, and turning technical infrastructure into clear and reliable user experiences, we would be glad to hear from you! Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior ML Engineer (AI Research)

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role This role is for Nebius AI R&D, a team focused on applied research in AI. Examples of applied research that we have recently published include: applying reinforcement learning for agent training in long-context multi-turn scenarios dramatically scaling task data collection to power reinforcement learning for SWE agents building a decontaminated evaluation for SWE agents that is regularly updated investigating how test-time guided search can be used to build more powerful agents The results often lead to collaboration with adjacent teams where our research findings are applied in practice. We are currently looking for senior- and staff-level ML engineers to work on research in areas such as: Guided search and reinforcement learning for agentic systems Reinforcement learning for reasoning models Web-scale problem collection for training agents Efficient model distillation Some examples of what your responsibilities might include are: Conducting experiments to figure out efficient ways to train a large language model on traces of interactions with various environments Exploring methods of guided generation and search in the trajectory space Coming up with ways to mine relevant data at web scale and figuring out efficient ways to use this data in model post-training Conducting experiments with different reinforcement learning configurations in verifiable domains Exploring methods to train AI agents on tasks with non-verifiable reward signals We expect you to have: A profound understanding of theoretical foundations of machine learning and reinforcement learning Deep expertise in modern deep learning for language processing and generation Substantial experience with training large models on multiple computational nodes Strong software engineering skills (we mostly use python) Deep experience with modern deep learning frameworks (we use jax) Strong communication and leadership abilities Experience designing, executing, and analyzing machine learning experiments with proper statistical rigor Ability to formulate research questions, design experiments to test hypotheses, and draw meaningful conclusions from results Ability to document research findings clearly and contribute to technical publications or report Nice to have: Experience with deep reinforcement learning for LLMs, including techniques such as reward modeling, DPO, PPO etc Familiarity with important ideas in LLM space, such as RoPE, ZeRO/FSDP, Flash Attention, quantization Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field Master’s or PhD preferred Track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment Experience in engineering complex systems, such as large distributed data processing systems or high-load web services Open-source projects that showcase your engineering prowess Excellent command of the English language, alongside superior writing, articulation, and communication skills Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior ML Engineer (Agentic Search)

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. We are seeking a Senior ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. Our focus is agentic search, where AI systems plan, retrieve and refine rather than just return results. You will develop and deploy machine learning models that power retrieval, ranking, and indexing at scale, helping AI systems access fresh, reliable information in real time. This is a high-impact role working on a production system used 24x7, operating at the scale of web search. Your responsibilities: Train and deploy ML models for retrieval, reranking, and search relevance, such as embedding models and cross-encoders, in production Develop models supporting crawling, data selection, and content understanding Build and maintain the data, training and evaluation pipelines behind our models: training-data generation, evaluation sets and retraining Contribute to and improve our ML platform: training and orchestration workflows (Kubernetes, GPU scheduling, experiment tracking, model lifecycle) and inference optimisation for low-latency serving Work closely with engineering to integrate and deploy ML models in production services, balancing latency, quality and cost Apply the latest architectural advances and training procedures for retrieval and LLM-integrated systems Must-haves: 5+ years of experience in software engineering or applied machine learning Strong programming skills in Python and at least one of Go or C++ Proven experience deploying ML models in production systems Solid understanding of machine learning and modern deep learning, including transformers and embeddings Experience building data or ML pipelines and working with workflow orchestration Ability to define meaningful model metrics and evaluate models rigorously Product-oriented mindset with a focus on impact and iteration Nice-to-haves: Hands-on experience with retrieval, ranking, or recommendation Experience with Kubernetes, distributed training or GPU scheduling, or inference optimisation (batching, quantisation, compilation) Contributions to open-source projects, technical publications, or conference talks Strong results on public benchmarks or leaderboards (e.g. MTEB, BEIR) or models released on Hugging Face Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Machine Learning Engineer, LLM Inference Optimization

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role As a Senior Machine Learning Engineer on the Applied AI team at Nebius Token Factory, you will own model and endpoint optimization from model artifacts through production deployment. Your work will span model internals, quantization and model compression, speculative decoding, KV-cache optimization, inference engines, serving architecture, and benchmarking to improve latency, throughput, memory efficiency, GPU utilization, and cost per token while preserving quality and reliability. You will work with kernel and platform engineers to investigate serving problems, compare configurations, and resolve performance and quality regressions. You will evaluate model- and engine-level optimizations together with distributed inference designs, including request routing, scheduling, prefill/decode coordination, and multi-node GPU execution. Your improvements will be validated through reproducible benchmarks and safe production rollouts under real-world workloads. Your responsibilities Own optimization projects for specific model families, customer endpoints, or serving backends. Compare inference engines and recommend serving configurations suited to individual workloads. Diagnose model-quality and performance regressions during production rollouts. Improve LLM and VLM endpoint latency, throughput, memory efficiency, GPU utilization, quality, and cost per token. Deploy, configure, benchmark, and extend engines such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, and NVIDIA Dynamo. Develop production model-compression workflows covering quantization, quantization-aware training, distillation, low-bit serving, and accuracy recovery. Implement or integrate speculative decoding, draft-model approaches, KV-cache optimization, prefix caching, chunked prefill, continuous batching, and disaggregated prefill/decode serving. For prefill–decode disaggregation (PDD), evaluate KV-cache transfer, worker placement, and capacity balancing to determine which workloads benefit from the architecture. Design and improve LLM request routers and scheduling policies that balance worker utilization, queueing, request characteristics, and KV-cache locality while meeting latency and reliability targets. Scale dense and mixture-of-experts inference across multiple GPU nodes. Select and tune tensor, pipeline, data, and expert parallelism—including wide expert parallelism (WideEP)—with attention to hardware topology, expert load balance, and communication overhead. Build reproducible benchmark harnesses measuring TTFT, TPOT, tokens per second per GPU, p95/p99 latency, GPU memory, reliability, and cost per token. Validate architecture choices under representative traffic and consistent GPU budgets. Collaborate with GPU kernel and platform engineers to trace bottlenecks across model code, kernels, runtime, scheduler, gateway, and cluster layers. Produce design documents, performance reports, rollout plans, and customer-facing technical explanations. Must-haves Strong engineering skills in Python and PyTorch. Hands-on experience deploying or optimizing LLM, VLM, or high-throughput transformer inference. Practical knowledge of at least one modern inference stack, such as vLLM, SGLang, TensorRT-LLM, Triton Inference Server, NVIDIA Dynamo, Ray Serve, KServe, or an equivalent internal system. A strong understanding of transformer inference bottlenecks involving KV cache, attention, memory bandwidth, batching, parallelism, and long-context serving. Ability to quantify trade-offs among latency, throughput, quality, utilization, and cost. Experience designing or optimizing distributed inference system architecture, with hands-on work in one or more areas such as request routing, distributed scheduling, PDD, multi-node inference, or expert parallelism. Strong communication and collaboration skills across research, kernel, infrastructure, product, and customer teams. Nice-to-haves Experience with quantization-aware training, post-training quantization, FP8, INT8, INT4, NVFP4, MXFP4, AWQ, GPTQ, or SmoothQuant. Experience with distillation, speculative decoding, EAGLE, Medusa, multi-token prediction, or related inference acceleration methods. Experience supporting agentic workloads involving tool calling, structured outputs, streaming APIs, high concurrency, and multi-step orchestration. Familiarity with CUDA or Triton; the role does not require kernel engineering to be the candidate’s primary specialization. Contributions to open-source projects such as vLLM, SGLang, TensorRT-LLM, FlashInfer, LMCache, PyTorch, Triton, Ray, or KServe. Implementation experience with cache-aware request routing, PDD, or WideEP, including diagnosing communication bottlenecks and load imbalance. Familiarity with GPU communication libraries and interconnects, such as NCCL, NVLink, InfiniBand, or RoCE. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Partner Solutions Architect

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. Customer experience Customer experience at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community. The role We are looking for an experienced Partner Solutions Architect with a proven track record of enabling both value-added resellers (VARs) and technology partners. You will help partners build differentiated offerings on Nebius, enable Channel joint value propositions and take those solutions to market. You will own the technical partner relationship, connecting partner sales, presales, product and engineering teams with their counterparts at Nebius. Combining cloud architecture expertise with commercial judgment, you will help partners win customers and grow adoption through repeatable solutions and effective enablement. You’re welcome to work from our office in Amsterdam or remotely from any EU country. Your responsibilities: Develop joint value propositions that combine Nebius with partner products or services, defining target customers, priority use cases, technical differentiation and business outcomes. Work with Channel and Nebius sales and marketing teams on joint go-to-market plans, account opportunities, co-selling activities, solution messaging and customer presentations. Lead joint customer discovery and solution discussions. Agree proof-of-concept success criteria and coordinate partner and Nebius specialists through technical validation and deployment planning. Enable VAR partners to qualify opportunities, position Nebius, design customer solutions and package their implementation or managed services around our platform. Help technology partners, including software vendors and data or AI platforms, define joint solutions, integration priorities and validation plans with their product and engineering teams. Build lasting relationships with partner engineering teams. Translate requirements and customer feedback into actionable plans, coordinate experts and influence product priorities. Track partner readiness, joint solution adoption and contributions to pipeline and customer wins. Use these results to improve enablement and scale successful partner activities. What you bring 5+ years in solutions architecture, technical presales or partner technical roles, with substantial experience supporting Channel and Technology partnerships. Demonstrated success enabling both VARs and technology partners, including examples of partners independently positioning solutions, pursuing opportunities or delivering joint offerings. Experience building joint value propositions and taking partner solutions to market, with evidence of customer wins, adoption growth or commercial impact. A track record of building partner enablement programs and adapting content for sales, presales and engineering audiences. Strong cloud architecture fundamentals across compute, storage, networking and security, with the ability to explain trade-offs and connect technical decisions to customer needs. Experience earning trust with partner engineering and product teams, working effectively with internal engineers and coordinating delivery across organizations without direct authority. Clear communication with engineers and business leaders, sound commercial judgment and an understanding of how resellers and technology partners make money. A relevant degree or equivalent professional experience, plus curiosity about AI infrastructure and the ability to learn new platforms quickly. Added bonuses The following experience would be valuable but is not required for the role: Hands-on Kubernetes and container platform experience, including deployment automation with tools such as Terraform. Experience with GPU-based workloads, HPC or distributed AI/ML workloads, including training, fine-tuning, inference or MLOps. Practical integration development using APIs, Python or infrastructure as code, or experience building reference implementations and technical demonstrations. Familiarity with AI software ecosystems or partner solutions built around major cloud and data platforms. I-PL1 Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior HPC Cluster Engineer

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role We’re looking for a Senior HPC Cluster Engineer to join our team and play a key role in the development of our cutting-edge hyperscaler platform. The GPU & InfiniBand team is responsible for enhancing and optimizing the core components of our Cloud platform, with a specific focus on GPU computing, InfiniBand networks, and the KVM/QEMU stack. You’ll work closely with hardware virtualization and device emulation technologies, ensuring high performance and security in multi-GPU, HPC environments. The role involves analyzing, troubleshooting, and improving infrastructure to support new hardware, fine-tuning system performance, and automating fault detection and resolution in a complex system. In this position, you will be responsible for: Tuning the performance of GPU clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments.  Analyzing and troubleshooting the root cause of issues related to GPUs and InfiniBand networks, and proposing corrective actions.  Integrating new hardware into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM.  Enhancing automation systems for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments.  Configuring and managing GPU devices and InfiniBand fabrics, ensuring efficient and reliable operation. We expect you to have: 5+ years of professional experience in system-level software development (focused on performance optimization, low-level programming).  3+ years of hands-on experience with Linux systems (administration, troubleshooting, and performance tuning).  In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems.  Strong proficiency in one or more performance-oriented programming languages (C/C++, Go, Python). It would be a plus if you have: Experience with GPU end-to-end testing in a cluster environment using InfiniBand networking.  Proven track record of analyzing and optimizing the performance of HPC workloads (e.g., simulations, data analysis, AI/ML workloads).  Familiarity with RDMA, RoCE, and InfiniBand protocols for high-performance communication.  Background in Software-Defined Networking (SDN) and experience with HPC cluster networking.  Understanding of QEMU/KVM virtualization and managing virtualized environments.  Experience with deep learning frameworks such as PyTorch and TensorFlow, and their integration with HPC systems.  Familiarity with collective communication libraries like MPI and NCCL for distributed computing. We conduct coding interviews as part of the process. #LI-LH2 Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior HPC Engineer, GPU Compute

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role We’re looking for a Senior HPC Cluster Engineer to join our team and play a key role in the development of our cutting-edge hyperscaler platform. The GPU & InfiniBand team is responsible for enhancing and optimizing the core components of our Cloud platform, with a specific focus on GPU computing, InfiniBand networks, and the KVM/QEMU stack. You’ll work closely with hardware virtualization and device emulation technologies, ensuring high performance and security in multi-GPU, HPC environments. The role involves analyzing, troubleshooting, and improving infrastructure to support new hardware, fine-tuning system performance, and automating fault detection and resolution in a complex system. In this position, you will be responsible for: Tuning the performance of GPU clusters and InfiniBand networks to ensure optimal operation in HPC and GPU-based environments.  Analyzing and troubleshooting the root cause of issues related to GPUs and InfiniBand networks, and proposing corrective actions.  Integrating new hardware into the existing infrastructure, including support for new GPU hardware through software stacks like Kubernetes, QEMU, and KVM.  Enhancing automation systems for proactive monitoring, detecting, and resolving issues in GPU and InfiniBand environments.  Configuring and managing GPU devices and InfiniBand fabrics, ensuring efficient and reliable operation. We expect you to have: 5+ years of professional experience in system-level software development (focused on performance optimization, low-level programming).  3+ years of hands-on experience with Linux systems (administration, troubleshooting, and performance tuning).  In-depth understanding of server architecture, including PCIe devices, NICs, Linux OS/Kernel, and high-performance computing (HPC) systems.  Strong proficiency in one or more performance-oriented programming languages (C/C++, Go, Python). It would be a plus if you have: Experience with GPU end-to-end testing in a cluster environment using InfiniBand networking.  Proven track record of analyzing and optimizing the performance of HPC workloads (e.g., simulations, data analysis, AI/ML workloads).  Familiarity with RDMA, RoCE, and InfiniBand protocols for high-performance communication.  Background in Software-Defined Networking (SDN) and experience with HPC cluster networking.  Understanding of QEMU/KVM virtualization and managing virtualized environments.  Experience with deep learning frameworks such as PyTorch and TensorFlow, and their integration with HPC systems.  Familiarity with collective communication libraries like MPI and NCCL for distributed computing. We conduct coding interviews as part of the process. #LI-LH2 Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Data Engineer

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role The Data Engineering team builds and operates the data platform that powers analytics, business intelligence, operational reporting, and data-driven products across Nebius. We ingest data from internal and external systems, develop reliable transformation pipelines and data models, and make trusted datasets available to business and product teams. We are looking for a Senior Data Engineer to own substantial parts of our data platform and deliver complex data products end to end. You will turn ambiguous business needs into pragmatic technical solutions, make architecture and implementation trade-offs, and improve the reliability, scalability, and usability of our data ecosystem. You will work closely with product, platform, and business teams, helping them use data effectively while ensuring that our systems remain maintainable and trustworthy as Nebius grows. Your responsibilities: Own the design, delivery, and operation of complex data pipelines, datasets, and platform components. Translate business and analytical requirements into scalable data models, reliable data products, and clear technical plans. Design and evolve data architecture, storage, processing, and orchestration patterns for large-scale workloads. Improve data quality, observability, lineage, and incident response for critical datasets and pipelines. Investigate and resolve challenging performance, reliability, and data-correctness issues in production. Establish reusable tools, conventions, and automation that improve engineering productivity and reduce operational risk. Work with product teams and business stakeholders to define data contracts, priorities, and success criteria. Contribute to technical direction through design reviews, thoughtful trade-offs, and documentation. Support and mentor other engineers through reviews, pairing, and knowledge sharing. Participate in the on-call rotation and take ownership of improving the operational health of the systems you support. Must-haves: 5+ years of experience in data engineering, backend engineering, or a related role; or equivalent experience delivering and operating production data systems. Proven experience independently delivering complex data pipelines or data-platform capabilities from problem definition through production operation. Strong Python and SQL skills, including writing maintainable production code and optimizing non-trivial queries. Hands-on experience with workflow orchestration tools such as Airflow, Prefect, or Dagster. Strong understanding of data modeling, including designing maintainable analytical models and data contracts for multiple consumers. Solid knowledge of data architectures and storage systems, including the trade-offs between different processing and storage approaches. Experience designing for reliability: testing, monitoring, data-quality validation, alerting, debugging, and incident resolution. Ability to make technical decisions under ambiguity, explain trade-offs clearly, and collaborate effectively with engineers and non-technical stakeholder Nice-to-haves: Experience with real-time or event-driven data platforms and streaming technologies. Experience building or operating cloud-native services with Docker and Kubernetes. Familiarity with Infrastructure as Code, particularly Terraform. Experience with data governance, access control, privacy, and compliance requirements such as GDPR or SOC 2. Experience with data observability and quality tools or frameworks, such as Great Expectations. Experience improving engineering standards through shared libraries, platform tooling, technical documentation, or mentoring. We conduct coding interviews as part of the process. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Customer AI Engineer - Token Factory

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role We're looking for a Senior Customer AI Engineer who will join our Token Factory team to help our customers successfully transition from proof-of-concept to production and scale their AI workloads on Nebius infrastructure. This role sits at the intersection of engineering, delivery, and customer success – ensuring that what was promised during pre-sales actually works reliably in production. You will work closely with customer engineering teams, Solution Architects, and Product/Infrastructure teams to drive stable, performant, and cost-efficient deployments. This role is NOT: A sales role (though you will support expansion through value) A pure support role (you won’t just react to tickets) A solution architect role (you won’t design systems from scratch) You’re welcome to work remotely from Europe. Your responsibilities will include: Own the production journey Lead the transition from PoC to production Ensure customer workloads are deployed, stable, and scalable Drive time-to-production and time-to-value Ensure technical success in production Understand customer architectures and use cases Monitor and improve:- performance (latency, throughput)- cost efficiency- reliability Identify and resolve bottlenecks proactively Act as a trusted technical partner Work directly with customer engineering teams Provide guidance on best practices and optimisation Translate technical challenges into actionable solutions Manage risks and incidents Act as a primary technical contact for production issues Coordinate with internal teams to resolve incidents Communicate clearly during high-pressure situations Drive continuous improvement Identify opportunities to optimise and expand usage Provide structured feedback to Product and Infrastructure teams Help shape better solutions based on real customer needs We expect you to have: Technical background Practical knowledge of inference frameworks (e.g. vLLM, TensorRT, or similar) Solid understanding of:- cloud or infrastructure systems- distributed systems or high-load applications- AI/ML workloads (LLMs, inference, etc.) is a strong plus Ability to troubleshoot and reason about system performance Customer-facing experience Experience working directly with technical customers (e.g. engineers, ML teams) Ability to communicate complex topics clearly and effectively Ownership & execution Strong sense of ownership – you drive outcomes, not just tasks Ability to manage multiple customers and priorities Structured, proactive, and solution-oriented mindset It will be an added bonus if you have: Experience with GPU workloads or AI infrastructure Background in solutions engineering, SRE, or technical support in B2B environments Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Senior Applied AI Solutions Engineer

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role AI is moving faster than any single product team can track. Nebius is expanding across serverless, databases, MLflow, MLOps, Physical AI, and HCLS — and customers arriving with complex, real-world ML workloads need more than documentation. This role exists to close that gap: someone who can prototype what's possible, accelerate customers through their first 90 days, and feed hard-won field insight back into the product roadmap.This role sits at the intersection of deep ML engineering and product impact. You'll spend roughly half your time in the field — helping new customers move from POC to production, running technical onboarding, and working hands-on through their ML stack. The other half you'll spend building — prototyping applied AI use cases that show what's possible on the platform, going deep on emerging techniques before they're mainstream, and turning that expertise into concrete product direction.This is not a presales role. You get your hands dirty every day. What success looks like in 12 months The product and sales teams have a library of working, polished demos they reach for on calls Enterprise customers you've touched have meaningfully faster time-to-value than those you haven't At least 2–3 product changes were shipped because of feedback you originated The team understands where applied AI is heading 6–12 months from now, partly because you told them Your responsibilities will include: Build prototypes and demos across the product portfolio — serverless inference, databases, MLflow, MLOps, and vertical use cases in Physical AI and HCLS — that become assets for sales, product, and engineering teams Support new customers hands-on through POC design, technical onboarding, and validation; act as the bridge between their ML team and the platform during the critical first months Go deep on emerging applied AI — new training techniques, inference optimizations, agentic architectures, new frameworks — and turn findings into working prototypes, writeups, and product recommendations Feed the product roadmap with specific, grounded feedback; be the voice of "here's what broke in three customer POCs last month and here's what needs to change" Develop reusable technical assets — notebooks, reference architectures, benchmark results — that reduce onboarding friction at scale We expect you to have: You've fine-tuned large models, debugged distributed training jobs, built production RAG or agentic pipelines, and optimized inference on GPU infrastructure — not just read about it You're fluent in the modern ML stack: PyTorch, HuggingFace, CUDA fundamentals, Kubernetes for ML, MLflow or equivalent, vector databases You've worked with enterprise ML teams — whether as a solutions engineer, customer engineer, or an ML engineer who collaborated closely with customers You read papers and implement them — not for credit, but because it's how you stay sharp You communicate with calibration: you can explain activation checkpointing tradeoffs to an ML engineer in the morning and the cost implication to a CTO in the afternoon It will be an added bonus if you have: Experience in any of our vertical domains: Physical AI / robotics / simulation, HCLS (drug discovery, medical imaging, clinical NLP), or enterprise AI application development Familiarity with MLOps at scale (Kubeflow, Metaflow, Argo, Ray) Prior work at a cloud provider or AI infrastructure company You've shared technical work publicly — notebooks, talks, blog posts that people actually use Who thrives here You'll thrive here if you're energized by variety — one day deep in a customer's MLOps stack, the next building a demo from scratch. You want your technical depth to influence product decisions, not just close deals. What we offer Competitive salary and comprehensive benefits package. Opportunities for professional growth within Nebius. Flexible working arrangements. A dynamic and collaborative work environment that values initiative and innovation. We're growing and expanding our products every day. If you're up to the challenge and are excited about AI and ML as much as we are, join us! Pay Transparency We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law. Base Compensation Range $200—$350,000 USD Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Security Solutions Engineer

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role We are seeking a Security Solutions Engineer with a strong background in strategic solution evaluation, vendor assessment, and hands-on Proof-of-Concept (PoC) validation. This role is a crucial bridge between identifying customer security requirements and implementing best-in-class, enterprise-grade solutions. You will be responsible for defining the criteria, researching the market, and executing technical validation for all major security tooling and services adopted by the company. Key responsibilities: 1. Strategic Research & Requirement Definition Threat-to-Solution Mapping: Proactively analyze customer expectations, regulatory/compliance drivers, and threat models to define precise functional and non-functional requirements for new security solutions. Market Analysis & Scouting: Conduct thorough market scans to identify cutting-edge security products, platforms, and vendors across key domains (e.g., CSPM/CNAPP, DLP, IAM/IGA, EDR/XDR, data security, Kubernetes security, and AI/ML security). Vendor Due Diligence: Evaluate potential vendors based on technical capability, security posture, integration requirements, roadmap, data residency/compliance, and support quality, and shortlist candidates for the PoC phase. 2. Technical Validation & Proof-of-Concept (PoC) Leadership PoC Planning & Design: Develop detailed, objective, and threat-aligned test plans and success criteria for all security solution Proof-of-Concepts (PoCs), including quantitative success metrics, coverage of key attack scenarios, and opportunities for automation. Hands-on Environment Setup: Independently architect and deploy isolated PoC environments that accurately simulate our production infrastructure (e.g., setting up cloud VPCs, Kubernetes clusters, integrating with test data via IaC, and mimicking typical workloads). Testing & Analysis: Execute security research methodologies within the PoC (e.g., simulating attack scenarios, conducting deep feature validation, assessing false positive/negative rates) to rigorously test the vendor solution's effectiveness. Artifact Generation: Document all findings, including technical performance data, integration challenges, security gaps discovered, and clear comparative analysis metrics. 3. Decision Support & Communication Recommendation & Insight: Deliver comprehensive, data-driven reports and compelling presentations to security and product leadership and engineering stakeholders, providing a clear recommendation for the optimal solution and vendor selection. Integration Planning: Work closely with Security Engineering, Platform/Infra, and DevOps teams to ensure selected solutions are feasible to integrate, operate, and scale, and to hand off PoC learnings into implementation plans. Must-haves: Experience: Minimum 6+ years in Security Engineering, Security Architecture, or a dedicated Security Research role focused on solution validation and vendor management. Technical Depth: Deep understanding of modern cloud security principles (e.g., AWS/Azure/GCP security models, Kubernetes/containers, network segmentation, IaC scanning, least privilege, identity-centric security, confidential computing). Programming and Automation - Strong scripting / programming skills (e.g., Python, Go, or similar) for automating PoCs, building test harnesses, and integrating tools via APIs and CI/CD pipelines. Solutions Expertise: Proven, hands-on experience with the architecture, deployment, and testing of two or more enterprise-grade security tools (e.g., SIEM/SOAR platforms, Endpoint Detection and Response (EDR), Vulnerability Management, Secrets Management). PoC Proficiency: Demonstrated ability to plan and execute complex technical Proof-of-Concepts, including setting up test environments and defining quantitative success metrics. Soft Skills: Exceptional analytical skills with the ability to translate complex technical findings into clear business risk and strategic recommendations. Strong written and verbal communication. Nice-to-haves: Experience in Cloud or Cloud-Heavy companies. Experience in a compliance-focused industry (e.g., finance, healthcare, or cloud infrastructure) and familiarity with frameworks such as ISO 27001, SOC 2, or GDPR. Advanced professional certifications such as CISSP, CCSK or relevant cloud certifications (e.g., AWS/GCP/Azure Security Specialty). Experience contributing to security standards, open-source tools, talks, or publications. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Remote

Product Manager - Anti Fraud

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role We run a large-scale GPU cloud and AI infrastructure platform. Fraud and abuse — stolen payment cards, fake sign-ups, compute mining, credential abuse, and coordinated free-tier exploitation — directly threaten platform economics, capacity availability for legitimate customers, and our standing with payment providers and cloud partners. As Product Manager, Anti-Fraud, you own the product roadmap for the systems that detect, prevent, and respond to fraud and abuse across the customer lifecycle — from onboarding and payment through to ongoing consumption. You sit at the intersection of Trust & Safety, Payments/Billing, Risk, Data Science, and Product Engineering, and you balance two goals in constant tension: stop bad actors and keep friction near zero for real customers. Your responsibilities will include: Own the end-to-end anti-fraud product roadmap: signup/KYC checks, payment fraud detection, account takeover protection, and compute-abuse (e.g., crypto mining, resource reselling) prevention. Own the rules and risk-scoring surfaces — the tooling that lets analysts and data scientists define, test, and deploy detection rules and ML models with clear guardrails and audit trails. Own the manual review and case-management experience for the Trust & Safety operations team, including queues, evidence views, and action workflows (block, limit, step-up verification, release). Own customer-facing friction points — verification flows, step-up challenges, and appeals — designed to minimize false positives and protect the legitimate user experience. Identify fraud and abuse incidents early — define the signals, alerts, and thresholds that surface incidents before they scale, and own the detection surface that flags them. Participate in incident reviews and post-mortems, capturing root causes and turning each finding into concrete improvements to detection rules, models, and the roadmap. Ensure timely response to active incidents — drive fast triage, clear ownership, and mitigation, working alongside Trust & Safety, Engineering, and Data Science to contain impact. Write clear PRDs and specs that translate fuzzy risk problems into shippable engineering and data-science work. Partner with Analytics team on detection models — defining the problem, labels, and success criteria, and deciding where rules vs. ML are the right tool. Run experiments and monitor rollouts, watching both fraud-catch metrics and false-positive / customer-friction impact. Work with Legal/Compliance to keep detection and enforcement aligned with payment-network rules, KYC/AML expectations, and data-privacy requirements. Track and report on fraud loss, chargeback rate, false-positive rate, review throughput, and time-to-detection. We expect you to have: Proven product management experience in fraud, risk, trust & safety, or payments. Strong analytical skills — comfortable with data, SQL or equivalent, and reasoning about precision/recall trade-offs and metrics. Ability to make decisions under ambiguity and to balance security, business, and customer-experience priorities. Solid collaboration with engineering and data science; you can hold a technical conversation about signals, features, and model behavior. Exposure to cloud, SaaS, marketplace, fintech, or infrastructure products. Understanding payment fraud, chargebacks, KYC/AML, or device/network signals (fingerprinting, velocity, IP reputation). It would be an added bonus if you have: Familiarity with ML-based detection systems and their operational lifecycle (drift, retraining, monitoring). Experience with abuse patterns specific to compute or GPU platforms (mining, credential stuffing, free-tier farming). Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

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