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. Location: Amsterdam Duration: 3 months Start date: January 2027 Compensation: Paid Eligibility: Current University student (Computer Science or related field), Recent Graduate or Early Career specialist Work authorization: Permitted to work in the job’s location The role We are looking for an early-career Frontend Engineer to turn complex infrastructure workflows into clear, maintainable user interfaces. You will contribute to production projects from your first weeks, learn alongside experienced engineers, and gradually take ownership of meaningful features. About the team We improve developer experience at Nebius in two complementary areas: Developer services: products and interfaces used by engineering teams across the company and, in some cases, by cloud customers. Frontend infrastructure: shared foundations and tooling used across our frontend codebase. Our users are Nebius engineers and cloud customers. We prioritize usability and reliability in everything we build. Your responsibilities : Developer services Design and build clear interfaces for complex infrastructure and operational workflows. Improve tools that help engineering teams test, release, and monitor services. Work with platform, infrastructure, and operations engineers to translate their needs into practical solutions. Frontend infrastructure Improve shared build systems, project tooling, libraries, templates, and test automation. Make shared tools straightforward for frontend engineers to adopt and use. Contribute to standards and documentation that help frontend teams work consistently. Across both areas Implement well-tested features from development through release. Write clear, maintainable code and participate in code reviews and technical discussions. Must-haves : Experience with at least one programming language, preferably TypeScript or Go. Experience building user interfaces with React through studies, an internship, personal projects, open-source contributions, or professional work. Practical experience with HTML and CSS. Experience using Git for version control. Strong problem-solving skills, curiosity, and openness to feedback. Clear communication skills and the ability to collaborate effectively in a distributed, cross-functional environment. Nice - to - have s : Familiarity with automated testing. Knowledge of common programming paradigms. An understanding of how programming languages differ and the trade-offs they make. 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. Please note that we are not actively hiring for this role at the moment. However, we are always interested in connecting with exceptional talent and would be happy to receive your application. If your experience aligns with future opportunities, we will keep your profile in our talent pool and get in touch when a suitable position becomes available. Summary: Location : Amsterdam Duration : 3 months Start date : 2027 Compensation : Paid Eligibility : Current University student (Computer Science or related field), Recent Graduate or Early Career specialist Work authorization : Permitted to work in the job’s location The role You’ll work alongside experienced engineers, learn how high-performance backend systems are designed and operated and contribute code that runs in real environments used by customers worldwide. You’ll get hands-on experience with modern backend technologies, scalable architectures and engineering best practices in a team that works at the cutting edge of AI cloud infrastructure. We expect you to have: Knowledge of at least one programming language (Go, Java, Python or С++). Understanding of basic algorithms and data structures. Strong motivation to learn, grow and develop as a backend engineer. Willingness to work with complex systems and ask questions. What we offer: Competitive salary and comprehensive benefits package. Mentorship from experienced AI, ML, and cloud infrastructure professionals. Hands-on experience with real customer workloads and production systems. Opportunities for professional growth within Nebius. A dynamic and collaborative work environment that values initiative and innovation. Opportunity to be considered for a full-time role after the Early Talent Program. 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! 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 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.

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 Token Factory is building an AI training and model post-training capability for frontier model improvement. This role owns the infrastructure that makes large-scale training and RL experiments possible, reliable, reproducible, and efficient. The work sits at the intersection of distributed systems, GPU performance, model training frameworks, RL pipelines, and production engineering. A Senior Machine Learning Engineer owns substantial ML work end to end. They can translate an ambiguous capability goal into concrete experiments, implement and debug training and RL recipes, build the supporting data and systems, and deliver measurable improvements in model quality, experiment throughput, and reliability. They are deeply hands-on and can independently debug both model-behavior failures and distributed training failures. Your responsibilities : Design and run model-training and post-training experiments, including SFT , continued pretraining, preference optimization ( DPO /IPO/ KTO ), and RL methods such as RLHF / RLAIF , PPO , and GRPO . Build reward functions, judge models, verifiers, task environments, and evaluation sets for reasoning, coding, tool use, and agentic workflows. Create synthetic data and data pipelines, including teacher-student generation, self-play, rejection sampling, filtering, and quality scoring. Analyze model-behavior failures and turn them into targeted data, reward, or algorithm improvements. Build and maintain distributed training and RL infrastructure using frameworks such as Megatron- LM , DeepSpeed, PyTorch FSDP /DTensor, Ray, verl, slime, AReaL, or OpenRLHF. Implement and debug parallelism strategies (tensor, pipeline, sequence/context, expert, and data parallelism) and build reliable rollout, reward-serving, checkpointing, and experiment-orchestration components. Profile and improve GPU utilization, memory usage, communication efficiency, training throughput, and inference/serving performance. Design rigorous evaluations and ablations for capability, instruction following, reasoning, tool use, safety, and regression risk. Write clear experiment plans, design docs, benchmark reports, and runbooks, and partner across research and platform teams. Must-haves : Strong Python and PyTorch engineering skills, with the ability to move quickly from idea to experiment to working system. Hands-on experience across at least two of: model training, post-training/ RL , applied modeling, data pipelines, or large-scale ML systems. Ability to design rigorous experiments with baselines, ablations, metrics, and failure analysis. Practical understanding of modern LLM behavior, instruction tuning, preference optimization, and evaluation challenges. Practical understanding of transformer training bottlenecks, memory pressure, communication overhead, and checkpointing. Ability to reason quantitatively about model quality, throughput, utilization, reliability, cost, and research velocity. Strong communication skills and ability to collaborate with researchers, engineers, and leadership. Nice - to - have s : Experience with LLM post-training, RL , agents, reward modeling, synthetic data, or model evaluation. Experience with RL frameworks or pipelines such as verl, slime, AReaL, OpenRLHF, TRL , or custom PPO / GRPO / RLHF systems. Experience with Megatron- LM , DeepSpeed, PyTorch FSDP /DTensor, Ray, Slurm, or Kubernetes on large GPU clusters. Familiarity with NCCL , CUDA , Triton, Nsight, InfiniBand/ RDMA , and H100/H200/B200 clusters, or with model serving and inference optimization. Publications, open-source contributions, or production impact in LLM post-training, RL , reasoning, coding models, synthetic data, distributed training, or evaluation. Experience designing agent environments, tool-use tasks, or verifier-based rewards. Key employee benefits in the US: 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. 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 $195,200 — $262,200 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 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 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. About Tavily We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent — but also informed. We work with some of the most innovative teams in AI — from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world. The Role: DevOps Engineer Managing Kubernetes clusters across multiple environments and regions Owning infrastructure as code for all resources Maintaining and improving CI/CD pipelines and GitOps-based deployments Maintaining and optimize real-time data pipelines that process billions of events per day across distributed queues and stream processors Building out monitoring, alerting, and observability Debugging production issues across services Managing cloud costs and capacity planning Working closely with a small engineering team — you'd own infra, not a slice of it What we're looking for 3+ years in a DevOps or platform engineering role, working in production environments Proven experience designing and operating large-scale, distributed systems, with a solid understanding of API design, reliability, and performance at scale Strong Kubernetes experience in a managed cloud environment Proficiency with infrastructure as code (Terraform or similar) Experience with GitOps-based deployment workflows Built or maintained observability stacks (logging, metrics, alerting) Experience handling production incidents calmly and methodically Nice to have: Multi-region deployments Search infrastructure Data pipeline experience (streaming, warehousing) Proxy/networking infrastructure at scale Why Tavily? Full ownership — small team, you own the entire infrastructure, not a slice of it Real scaling challenges — bursty scraping workloads, cache invalidation, multi-region, millions of daily requests AI-native company — your infra directly powers AI agents used by leading companies in the space. 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. Summary: We are seeking an AI Full-Stack Developer to build and scale automation solutions across internal company processes using AI, LLMs, and agent-based systems. This role focuses on delivering practical automation solutions, integrating AI capabilities with internal tools, and orchestrating workflows across multiple systems, with a dynamic range of tasks that offer both quick wins and complex challenges. Responsibilities: Build AI-driven automation solutions using LLMs, APIs, and agent frameworks. Develop systems to automate document processing, data extraction, and operational workflows. Design and implement multi-step automated workflows connecting AI models and internal services. Integrate automation solutions with internal systems such as HR, finance, legal, dashboards, and ticketing tools. Deliver and iterate practical automation solutions swiftly, from simple GPT/AI integrations to complex workflows. Train and support internal teams on newly built or optimized systems for strong adoption and self-sufficiency. Collaborate with Technical Team Lead, Product Manager, and IT teams on architecture and system integration. Communicate clearly with internal stakeholders and external partners or vendors. Required Skills: 5+ years of experience working as a Full-Stack Developer Strong programming skills in Python, TypeScript, JavaScript, and React. Experience building backend services and API integrations. Practical experience with LLM APIs or AI-based services. Strong familiarity with AI developer ecosystems. Proven ability to use AI-assisted coding tools effectively. Ability to work independently and efficiently. Familiarity with workflow automation systems or distributed architectures. Preferred Qualifications: Experience building AI agents or multi-step AI workflows. Experience with prompt engineering or LLM orchestration frameworks. Experience integrating with enterprise systems or internal business tools. Familiarity with event-driven architectures, queues, and task orchestration systems. Experience in teaching non-technical users how to utilize developed systems effectively. 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.