Careers at Nebius Group

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 an IT Infrastructure Engineer – RMA & Hardware Diagnostics to own advanced hardware troubleshooting and RMA lifecycle management within our production data center environments. This role serves as the escalation point for complex server and firmware-related issues that impact system reliability and fleet availability. You will be responsible for deep diagnostics across enterprise server platforms, performing structured root cause analysis, validating failed components, and managing end-to-end warranty replacement processes with OEM vendors. This is a hands-on technical role with direct impact on hardware reliability, SLA performance, and operational scalability. You will work on-site in one of our data centers, collaborating closely with L1/L2 technicians, infrastructure engineers, and vendors to reduce repeat failures and improve overall hardware quality across the fleet. *]:pointer-events-auto R6Vx5W_threadScrollVars scroll-mb-[calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" data-turn-id="request-69e2a372-fb84-8336-9e1a-01cc950eb9db-55" data-turn-id-container="request-69e2a372-fb84-8336-9e1a-01cc950eb9db-55" data-testid="conversation-turn-606" data-scroll-anchor="false" data-turn="assistant"> You will work out of our Minnesota data center location. Your responsibilities will include: Perform advanced firmware and hardware diagnostics on enterprise server platforms, including CPU, memory, PCIe devices, GPUs, storage subsystems, and power components Troubleshoot complex hardware failures using system logs, BMC/IPMI interfaces, BIOS diagnostics, and vendor-specific tooling Act as the primary escalation point for L1 and L2 technicians on high-impact hardware incidents Conduct structured root cause analysis and document findings to prevent repeat failures Own the full RMA lifecycle, including validation of failed components, warranty claim creation, vendor coordination, tracking, and resolution Interface directly with OEM vendors to escalate recurring hardware defects and drive corrective action Analyze hardware failure trends and report metrics such as repeat RMA rates and component reliability Develop and standardize diagnostic playbooks, troubleshooting workflows, and hardware validation procedures Validate replacement components prior to redeployment into production environments Collaborate cross-functionally with data center operations, procurement, and engineering teams to improve hardware lifecycle processes Contribute to reducing MTTR and improving fleet-wide reliability through process improvements and knowledge sharing We expect you to have: 5+ years of hands-on experience working with enterprise server hardware in a production data center environment Deep understanding of x86 server architecture, including CPUs, memory, PCIe devices, storage controllers, GPUs, and power subsystems Strong experience performing firmware and BIOS/BMC diagnostics and upgrades Advanced Linux command-line troubleshooting skills, including log analysis and hardware-level diagnostics Experience working with remote management interfaces such as IPMI, iDRAC, iLO, or equivalent Proven experience managing hardware RMA processes and working directly with OEM vendors Ability to conduct structured root cause analysis and document technical findings clearly Familiarity with hardware monitoring systems and failure trend analysis Strong ownership mindset and ability to operate independently in mission-critical environments High proficiency in spoken and written English It will be an added bonus if you have: Experience performing board-level diagnostics and component-level repair (SMD rework) Familiarity with data center networking equipment and basic network troubleshooting Experience supporting GPU-dense or high-performance compute environments Valid driver’s license Compensation We offer competitive salaries, ranging from $112,700.00 - $140,800.00 OTE (On Target Earnings) based on your experience and skills. 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.

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 Lead Software Systems Engineer - GPU Performance 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. Key employee benefits: Health insurance: 100% company-paid medical, dental and vision coverage for employees and families. 401(k) plan: Up to 4% company match with immediate vesting. Parental leave : 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers. Remote work reimbursement: Up to $85/month for mobile and internet. Disability & life insurance: Company-paid short-term, long-term and life insurance coverage. #LI-LH2 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 $170,000 — $300,000 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.

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 highly skilled ML/AI Engineer to join our team to lead and support benchmarking of GPU platforms benchmarking of GPU platforms for machine learning and AI workloads. You will play a critical role in evaluating the performance of GPU-based hardware for various deep learning and AI frameworks, enabling data-driven decisions for platform optimisation and next-generation hardware development. Your responsibilities will include: Work closely with hardware, development teams to profile and analyse GPU performance at the system and kernel level. Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g.,CUDA, ROCm). Debug and optimise ML workloads to run efficiently on GPU hardware, identifying and resolving performance bottlenecks. Perform acceptance testing acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads. Perform experiments across diverse GPU system configurations to assess the impact of varying interconnect strategies and system-level optimisations on performance and scalability. Develop tools and dashboards to visualise performance metrics visualise performance metrics, bottlenecks, and trends. Contribute to internal tooling, frameworks, and best practices We expect you to have: A profound understanding of theoretical foundations of machine learning Deep understanding of performance aspects of large neural networks training and inference (data/tensor/context/expert parallelism, offloading, custom kernels, hardware features, attention optimisations, dynamic batching etc.) Deep experience with modern deep learning frameworks (PyTorch, JAX, Megatron-LM, Tensort-LLM) Good understanding of the GPU stack: CUDA,NCCL, drivers, and relevant libraries Familiarity with containerized environments (e.g., Docker, Kubernetes). Strong communication and ability to work independently Ways to stand out from the crowd: Familiarity with modern LLM inference frameworks (vLLM, SGLang, TensorRT) Experience in Python and performance profiling tools (e.g., Nsight, nvprof, perf). Familiarity with cloud ML platforms like AWS, GCP, Azure ML Contributions to open-source ML benchmarking tools 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.

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 highly skilled ML/AI Engineer to join our team to lead and support benchmarking of GPU platforms benchmarking of GPU platforms for machine learning and AI workloads. You will play a critical role in evaluating the performance of GPU-based hardware for various deep learning and AI frameworks, enabling data-driven decisions for platform optimisation and next-generation hardware development. Your responsibilities will include: Work closely with hardware, development teams to profile and analyse GPU performance at the system and kernel level. Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g.,CUDA, ROCm). Debug and optimise ML workloads to run efficiently on GPU hardware, identifying and resolving performance bottlenecks. Perform acceptance testing acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads. Perform experiments across diverse GPU system configurations to assess the impact of varying interconnect strategies and system-level optimisations on performance and scalability. Develop tools and dashboards to visualise performance metrics visualise performance metrics, bottlenecks, and trends. Contribute to internal tooling, frameworks, and best practices We expect you to have: A profound understanding of theoretical foundations of machine learning Deep understanding of performance aspects of large neural networks training and inference (data/tensor/context/expert parallelism, offloading, custom kernels, hardware features, attention optimisations, dynamic batching etc.) Deep experience with modern deep learning frameworks (PyTorch, JAX, Megatron-LM, Tensort-LLM) Good understanding of the GPU stack: CUDA,NCCL, drivers, and relevant libraries Familiarity with containerized environments (e.g., Docker, Kubernetes). Strong communication and ability to work independently Ways to stand out from the crowd: Familiarity with modern LLM inference frameworks (vLLM, SGLang, TensorRT) Experience in Python and performance profiling tools (e.g., Nsight, nvprof, perf). Familiarity with cloud ML platforms like AWS, GCP, Azure ML Contributions to open-source ML benchmarking tools 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.

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 highly skilled ML/AI Engineer to join our team to lead and support benchmarking of GPU platforms benchmarking of GPU platforms for machine learning and AI workloads. You will play a critical role in evaluating the performance of GPU-based hardware for various deep learning and AI frameworks, enabling data-driven decisions for platform optimisation and next-generation hardware development. Your responsibilities will include: Work closely with hardware, development teams to profile and analyse GPU performance at the system and kernel level. Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g.,CUDA, ROCm). Debug and optimise ML workloads to run efficiently on GPU hardware, identifying and resolving performance bottlenecks. Perform acceptance testing acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads. Perform experiments across diverse GPU system configurations to assess the impact of varying interconnect strategies and system-level optimisations on performance and scalability. Develop tools and dashboards to visualise performance metrics visualise performance metrics, bottlenecks, and trends. Contribute to internal tooling, frameworks, and best practices We expect you to have: A profound understanding of theoretical foundations of machine learning Deep understanding of performance aspects of large neural networks training and inference (data/tensor/context/expert parallelism, offloading, custom kernels, hardware features, attention optimisations, dynamic batching etc.) Deep experience with modern deep learning frameworks (PyTorch, JAX, Megatron-LM, Tensort-LLM) Good understanding of the GPU stack: CUDA,NCCL, drivers, and relevant libraries Familiarity with containerized environments (e.g., Docker, Kubernetes). Strong communication and ability to work independently Ways to stand out from the crowd: Familiarity with modern LLM inference frameworks (vLLM, SGLang, TensorRT) Experience in Python and performance profiling tools (e.g., Nsight, nvprof, perf). Familiarity with cloud ML platforms like AWS, GCP, Azure ML Contributions to open-source ML benchmarking tools 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.

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 Nebius is looking for an experienced Security Architect Manager to join the Cyber Security organization, reporting to the Head of Security Engineering uner the CISO. This role is responsible for leading the organization’s security architecture across corporate networks and cloud environments, ensuring secure design and implementation of enterprise infrastructure at scale. The ideal candidate combines deep expertise in network and cloud security with strong leadership capabilities. You will define and drive security architecture across hybrid environments, working closely with IT, Infrastructure, Network, DevOps, and Security teams to ensure robust, scalable, and resilient security controls. Your responsibilities will include: Lead and manage the security architecture domain, including security architects and/or senior engineers. Define and maintain security architecture standards, guidelines, and reference designs across corporate and cloud environments. Act as the primary authority on enterprise security architecture across networks, identity, endpoints, and cloud platforms. Design and evolve secure enterprise network architectures, including segmentation, Zero Trust, and hybrid connectivity. Define and enforce security controls for corporate networks, data centers, and remote access solutions (ZTNA, proxies, NAC). Lead architecture and selection of network security technologies (e.g., firewalls, secure gateways, access control solutions). Lead security architecture across cloud platforms and hybrid environments. Define secure reference architectures for cloud networking, identity, and workload protection. Ensure proper implementation of cloud security controls, including IAM, segmentation, encryption, and monitoring. Define security architecture for endpoints and identity, including EDR/XDR, device hardening, SSO, MFA, and privileged access. Ensure secure baseline configurations and access control mechanisms across corporate and cloud environments. Identify architectural risks and security gaps and drive mitigation strategies across infrastructure and cloud environments. Establish and enforce architecture review processes and governance for new systems and changes. Collaborate with SOC, Vulnerability Management, IT, and Infrastructure teams to improve overall security posture. Contribute to the cyber security strategy and roadmap, including adoption of modern models such as Zero Trust. We expect you to have: 7+ years of experience in cyber security, with a strong focus on cloud security. 2+ years of experience leading or managing security architects or senior security engineers. Deep expertise in enterprise network security (firewalls, segmentation, VPN, proxies, NAC, etc.). Strong hands-on experience with cloud platforms (AWS, GCP, Azure) and cloud security best practices. Strong understanding of identity and access management (IAM), Active Directory / Entra ID, and privileged access controls. Experience securing hybrid environments (on-premise + cloud). Hands-on experience with enterprise security technologies (e.g., Palo Alto, Check Point, Cisco, Zscaler, CrowdStrike, Microsoft Defender). Strong understanding of Zero Trust architecture principles. Experience working cross-functionally with IT, Infrastructure, Network, DevOps, and Security teams. Excellent analytical, problem-solving, and communication skills in English. It will be an added bonus if you have: Experience designing and implementing Zero Trust or network segmentation programs. Familiarity with cloud-native security tools (e.g., Wiz, Prisma Cloud, Defender for Cloud). Experience with enterprise identity platforms (Entra ID / Azure AD, Okta, etc.). Knowledge of regulatory and compliance frameworks (ISO 27001, SOC 2, NIST, etc.). Experience in large-scale enterprise or high-growth environments. Relevant certifications such as CISSP, CCSP, or equivalent. BSc in Computer Science, Information Security, or a related field. 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.

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 Nebius is looking for an experienced Security Architect Manager to join the Cyber Security organization, reporting to the Head of Security Engineering uner the CISO. This role is responsible for leading the organization’s security architecture across corporate networks and cloud environments, ensuring secure design and implementation of enterprise infrastructure at scale. The ideal candidate combines deep expertise in network and cloud security with strong leadership capabilities. You will define and drive security architecture across hybrid environments, working closely with IT, Infrastructure, Network, DevOps, and Security teams to ensure robust, scalable, and resilient security controls. Your responsibilities will include: Lead and manage the security architecture domain, including security architects and/or senior engineers. Define and maintain security architecture standards, guidelines, and reference designs across corporate and cloud environments. Act as the primary authority on enterprise security architecture across networks, identity, endpoints, and cloud platforms. Design and evolve secure enterprise network architectures, including segmentation, Zero Trust, and hybrid connectivity. Define and enforce security controls for corporate networks, data centers, and remote access solutions (ZTNA, proxies, NAC). Lead architecture and selection of network security technologies (e.g., firewalls, secure gateways, access control solutions). Lead security architecture across cloud platforms and hybrid environments. Define secure reference architectures for cloud networking, identity, and workload protection. Ensure proper implementation of cloud security controls, including IAM, segmentation, encryption, and monitoring. Define security architecture for endpoints and identity, including EDR/XDR, device hardening, SSO, MFA, and privileged access. Ensure secure baseline configurations and access control mechanisms across corporate and cloud environments. Identify architectural risks and security gaps and drive mitigation strategies across infrastructure and cloud environments. Establish and enforce architecture review processes and governance for new systems and changes. Collaborate with SOC, Vulnerability Management, IT, and Infrastructure teams to improve overall security posture. Contribute to the cyber security strategy and roadmap, including adoption of modern models such as Zero Trust. We expect you to have: 7+ years of experience in cyber security, with a strong focus on cloud security. 2+ years of experience leading or managing security architects or senior security engineers. Deep expertise in enterprise network security (firewalls, segmentation, VPN, proxies, NAC, etc.). Strong hands-on experience with cloud platforms (AWS, GCP, Azure) and cloud security best practices. Strong understanding of identity and access management (IAM), Active Directory / Entra ID, and privileged access controls. Experience securing hybrid environments (on-premise + cloud). Hands-on experience with enterprise security technologies (e.g., Palo Alto, Check Point, Cisco, Zscaler, CrowdStrike, Microsoft Defender). Strong understanding of Zero Trust architecture principles. Experience working cross-functionally with IT, Infrastructure, Network, DevOps, and Security teams. Excellent analytical, problem-solving, and communication skills in English. It will be an added bonus if you have: Experience designing and implementing Zero Trust or network segmentation programs. Familiarity with cloud-native security tools (e.g., Wiz, Prisma Cloud, Defender for Cloud). Experience with enterprise identity platforms (Entra ID / Azure AD, Okta, etc.). Knowledge of regulatory and compliance frameworks (ISO 27001, SOC 2, NIST, etc.). Experience in large-scale enterprise or high-growth environments. Relevant certifications such as CISSP, CCSP, or equivalent. BSc in Computer Science, Information Security, or a related field. 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.

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 Applied ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. 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, tackling challenges comparable to large-scale web search. Your responsibilities: Design, train, and deploy ML models for retrieval, reranking, and search relevance in production Build and optimise embedding-based indexing and large-scale retrieval systems Develop models supporting crawling, data selection, and content understanding Define and improve quality metrics for agent-native search and build evaluation pipelines Work on systems operating at very large scale, including high-throughput query workloads Collaborate closely with engineering teams to integrate ML models into production services Analyse performance trade-offs across latency, quality, and cost Experiment with and apply state-of-the-art techniques in search, retrieval, and LLM-integrated systems Contribute to product and architectural decisions in a fast-moving environment Must-haves: 5+ years of experience in software engineering or applied machine learning Strong programming skills in Python, Go, or C++ Proven experience deploying ML models in production systems Hands-on experience with retrieval, ranking, recommendation, or similar ML problems Strong understanding of machine learning and modern deep learning techniques Experience working with large-scale data systems and high-throughput environments Ability to design evaluation frameworks and define meaningful model metrics Product-oriented mindset with a focus on impact and iteration Strong problem-solving skills and ability to work in a distributed team Nice-to-haves: Experience with search systems or large-scale information retrieval Familiarity with embeddings, transformers, and modern NLP systems Experience working on LLM-powered or agent-based systems Contributions to open-source projects, technical publications, or conference talks Participation in competitive ML (e.g. Kaggle) or similar signals of strong technical ability 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.

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 Applied ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. 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, tackling challenges comparable to large-scale web search. Your responsibilities: Design, train, and deploy ML models for retrieval, reranking, and search relevance in production Build and optimise embedding-based indexing and large-scale retrieval systems Develop models supporting crawling, data selection, and content understanding Define and improve quality metrics for agent-native search and build evaluation pipelines Work on systems operating at very large scale, including high-throughput query workloads Collaborate closely with engineering teams to integrate ML models into production services Analyse performance trade-offs across latency, quality, and cost Experiment with and apply state-of-the-art techniques in search, retrieval, and LLM-integrated systems Contribute to product and architectural decisions in a fast-moving environment Must-haves: 5+ years of experience in software engineering or applied machine learning Strong programming skills in Python, Go, or C++ Proven experience deploying ML models in production systems Hands-on experience with retrieval, ranking, recommendation, or similar ML problems Strong understanding of machine learning and modern deep learning techniques Experience working with large-scale data systems and high-throughput environments Ability to design evaluation frameworks and define meaningful model metrics Product-oriented mindset with a focus on impact and iteration Strong problem-solving skills and ability to work in a distributed team Nice-to-haves: Experience with search systems or large-scale information retrieval Familiarity with embeddings, transformers, and modern NLP systems Experience working on LLM-powered or agent-based systems Contributions to open-source projects, technical publications, or conference talks Participation in competitive ML (e.g. Kaggle) or similar signals of strong technical ability 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.

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 Applied ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. 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, tackling challenges comparable to large-scale web search. Your responsibilities: Design, train, and deploy ML models for retrieval, reranking, and search relevance in production Build and optimise embedding-based indexing and large-scale retrieval systems Develop models supporting crawling, data selection, and content understanding Define and improve quality metrics for agent-native search and build evaluation pipelines Work on systems operating at very large scale, including high-throughput query workloads Collaborate closely with engineering teams to integrate ML models into production services Analyse performance trade-offs across latency, quality, and cost Experiment with and apply state-of-the-art techniques in search, retrieval, and LLM-integrated systems Contribute to product and architectural decisions in a fast-moving environment Must-haves: 5+ years of experience in software engineering or applied machine learning Strong programming skills in Python, Go, or C++ Proven experience deploying ML models in production systems Hands-on experience with retrieval, ranking, recommendation, or similar ML problems Strong understanding of machine learning and modern deep learning techniques Experience working with large-scale data systems and high-throughput environments Ability to design evaluation frameworks and define meaningful model metrics Product-oriented mindset with a focus on impact and iteration Strong problem-solving skills and ability to work in a distributed team Nice-to-haves: Experience with search systems or large-scale information retrieval Familiarity with embeddings, transformers, and modern NLP systems Experience working on LLM-powered or agent-based systems Contributions to open-source projects, technical publications, or conference talks Participation in competitive ML (e.g. Kaggle) or similar signals of strong technical ability 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.