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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. Role Summary We are looking for a Network Security Engineer to join our Network team. This role combines deep expertise in network engineering and cybersecurity. You will help implement end-to-end network security architectures for enterprise and data center backbone/fabric environments, work with network architects and the management team to guide these designs through review and approval with the Security team, and operate and maintain the implemented solutions day-to-day. You are expected to be hands-on with leading firewall platforms (Palo Alto, Check Point, etc.), understand complex routing and switching designs, and be comfortable implementing and troubleshooting these networks. Responsibilities Implement and maintain Zero Trust-aligned security architectures for both enterprise and data center networks. Configure Layer 3/4 & Multi-VRF Segmentation, Security Policies, Secure Remote access. Implement and test large hyper scale DC Security solutions : IPS/NDR solutions , AntiDDOS solutions. Integrate NGFW platforms with modern identity providers such as Microsoft Entra ID and Okta, maintain NGFW management, automation, and logging capabilities required by the Security team. Implement and maintain Security Capabilities, including Layer 7 application inspection, IPS, user identification, ZTNA, and SASE integrations. Integrate and operate monitoring tools such as Zabbix, Grafana, and Akvorado. Regularly perform security hardening, vulnerability management, and patching and upgrades on network and infrastructure devices, and verify the effectiveness of these procedures. Required Qualifications Experience in networking and security protocols (TCP/IP, HTTP(S), DNS, TLS, IPsec, Routing protocols ) Experience and Knowledge of Backbone & Datacenter technologies (EVPN, L3VPN MPLS, MPBGP, L2VPN..) Hands-on experience with next-generation firewalls (Palo Alto Networks, Check Point, or similar). Experience with automation using Python, Go, or equivalent. Proficiency in Unix/Linux and experience with major network vendors (Cisco, Juniper, Aruba, etc.). Experience configuring and troubleshooting NGFW capabilities and integrations, including IPS, User-ID, Microsoft Entra ID, and ZTNA. Preferred Qualifications Good knowledge of IPv6. Experience with automation tools (Ansible, Terraform, NetBox, SaltStack, etc.). Experience with large-scale, highly available distributed systems. Knowledge of Zero Trust principles and micro-segmentation approaches. Relevant certifications (CCNP/CCIE, PCNSE, NSE 4/7) and professional working proficiency in English. Familiarity with commercial or open-source monitoring, logging, and security analytics solutions such as Splunk; EDR/XDR platforms such as CrowdStrike; and centralized NGFW management platforms such as Panorama, Strata Cloud Manager, and FortiManager. Bonus: Exposure to DevSecOps practices (SAST/DAST), CSPM/CWPP platforms such as Wiz, EDR, offensive security (OSCP/CPTS, red teaming), or security frameworks, standards, and regulations such as ISO/IEC 27001, NIST CSF, and GDPR. 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 to join the Cyber Security organization, reporting to the Security Architect Manager. This role focuses on designing and implementing secure architectures across corporate networks and cloud environments. You will play a key role in defining secure solutions, reviewing system designs, and ensuring security is embedded across enterprise infrastructure. The ideal candidate brings strong hands-on expertise in network and cloud security, along with the ability to work closely with IT, Infrastructure, DevOps, and Engineering teams to drive secure and scalable implementations. You’re welcome to work in our offices in Amsterdam. Your responsibilities will include: Design and implement secure architectures across corporate networks, cloud platforms, and hybrid environments. Define and maintain security standards, guidelines, and reference architectures aligned with organizational requirements. Review and approve architecture and design of new systems, infrastructure, and network changes. Design and support secure enterprise network architectures, including segmentation, Zero Trust, and remote access solutions. Define and implement controls for firewalls, ZTNA, proxies, and network access control (NAC). Design secure cloud architectures including IAM, networking, and workload protection. Ensure proper implementation of cloud security controls such as segmentation, encryption, and monitoring. Define and support identity and access management controls, including SSO, MFA, and privileged access. Contribute to endpoint security architecture, including EDR/XDR and device hardening standards. Identify security risks and architectural gaps and recommend mitigation strategies. Participate in architecture reviews, risk assessments, and security design discussions. Collaborate with SOC, Vulnerability Management, IT, and Engineering teams to improve overall security posture. Support implementation of security architecture initiatives and improvements across the organization. We expect you to have: 5+ years of experience in cyber security, with a focus on cloud security, networks, and/or SDLC Experience working with cloud platforms (AWS, GCP, Azure) and cloud security best practices. Strong hands-on experience in enterprise network security (firewalls, segmentation, VPN, proxies, NAC, etc.). Solid understanding of identity and access management (IAM), Active Directory / Entra ID, and access control models. Experience working in hybrid environments (on-premise + cloud). Strong understanding of security architecture principles and risk-based design. Experience working cross-functionally with IT, Infrastructure, DevOps, and Engineering teams. Strong analytical and problem-solving skills. It will be an added bonus if you have: Experience with Zero Trust architecture and network segmentation strategies. Familiarity with cloud security tools (e.g., Wiz). 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 SaaS, cloud-native, or enterprise-scale 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. The role 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 & fine-tuning platform that makes every kind of foundation model — text, vision, audio, and emerging multimodal architectures — fast, reliable, and effortless to train & deploy at massive scale. Some directions we currently working on and which you can be a part of: Advanced Fine-Tuning: Enhancing fine-tuning methodologies - both LoRA-based and full-parameter - for cutting-edge LLMs (e.g., GPT-OSS, Kimi K2.5, DeepSeek V3.1/V3.2, GLM-4.7), focusing on both model quality and training efficiency. Inference Optimization: Identifying LLM inference bottlenecks to drive production speedups. This involves building model training and evaluation pipelines in JAX for speculative decoding, experimenting with architectures (dense/MoE, auto-regressive/parallel), and deriving scaling laws to guide resource allocation. Low Precision Training & Inference: Investigating low-precision (FP8, NVFP4/MXFP4) methodologies for supervised fine-tuning and reinforcement learning - spanning both inference and training - optimized for modern hardware 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 Experience with training large models on multiple computational nodes Reasonable understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.) Strong software engineering skills (we mostly use Python) Deep experience with modern deep learning frameworks (we use JAX) Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing Strong communication and leadership abilities Nice to have: Previous experience working with language models or other similar NLP technologies. Familiarity with important ideas in LLM space, such as MHA, RoPE, ZeRO/FSDP, Flash Attention, quantization A track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment. Strong engineering skills, including experience in developing large distributed 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. 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.