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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. 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. The role: The role involves forming technical hypotheses, designing targeted tests, analyzing system logs and low-level hardware data, and distinguishing between GPU, host, firmware, interconnect, thermal, and physical hardware failures. It requires strong ownership, curiosity, and the ability to turn ambiguous problems into evidence-based conclusions and repeatable troubleshooting procedures. This is a senior systems engineering role focused on diagnosing and resolving complex hardware and platform failures in high-performance AI infrastructure. This engineer will work across Linux, GPU servers, PCIe, firmware, power, and cooling to determine the true root cause of issues that may not have an existing troubleshooting procedure. What skills we expect you to have: Minimum 5 years of hands-on systems engineering experience across Linux, server hardware, firmware, PCIe, and GPU or high-performance computing platforms. Extensive Linux experience, particularly using Linux as an environment for hardware debugging, system-level troubleshooting, and platform investigation. Knowledge of the Linux kernel and experience with kernel-level debugging or troubleshooting. Strong knowledge of modern server architecture, particularly in high-performance, GPU-based environments. Strong knowledge of NVIDIA GPU platforms and diagnostic tooling, including nvidia-smi, XID and SXID analysis, GSP and driver behaviour, NVLink, NVSwitch, Fabric Manager, DCGM diagnostics, and NCCL testing Deep knowledge of PCIe, including topology, enumeration, root complexes, endpoints, switches, bridges, retimers, link speed and width, AER and DPC errors, completion timeouts, and link failures. Candidates should understand how protocol-level errors can relate to physical-layer or signal-integrity problems. Experience benchmarking systems for performance, stability, power efficiency, thermal behaviour, and workload characteristics In depth understanding of firmware interactions across BIOS/UEFI, BMC, CPLD/FPGA, GPU firmware, NIC firmware, and other platform components. Experience with low-level hardware communication and debugging using I²C, SMBus, PMBus, register maps, bit masks, byte- and word-level data, and device datasheets. Demonstrated ability to troubleshoot complex hardware, software, and networking issues. Experience with deep problem investigation, root cause analysis, and performance optimization in cloud or high-performance computing environments. Strong analytical and problem-solving skills with a performance-first mindset. Scripting and automation using various languages (Python\Go) 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. Compensation We offer a competitive salary ranging from $179,500- $224,300 + quarterly performance bonuses. Join Nebius Today! 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.

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. The role The Data Engineering team builds and operates the data platform that powers analytics, business intelligence, operational reporting, and data-driven products across Nebius. We ingest data from internal and external systems, develop reliable transformation pipelines and data models, and make trusted datasets available to business and product teams. We are looking for a Senior Data Engineer to own substantial parts of our data platform and deliver complex data products end to end. You will turn ambiguous business needs into pragmatic technical solutions, make architecture and implementation trade-offs, and improve the reliability, scalability, and usability of our data ecosystem. You will work closely with product, platform, and business teams, helping them use data effectively while ensuring that our systems remain maintainable and trustworthy as Nebius grows. Your responsibilities : Own the design, delivery, and operation of complex data pipelines, datasets, and platform components. Translate business and analytical requirements into scalable data models, reliable data products, and clear technical plans. Design and evolve data architecture, storage, processing, and orchestration patterns for large-scale workloads. Improve data quality, observability, lineage, and incident response for critical datasets and pipelines. Investigate and resolve challenging performance, reliability, and data-correctness issues in production. Establish reusable tools, conventions, and automation that improve engineering productivity and reduce operational risk. Work with product teams and business stakeholders to define data contracts, priorities, and success criteria. Contribute to technical direction through design reviews, thoughtful trade-offs, and documentation. Support and mentor other engineers through reviews, pairing, and knowledge sharing. Participate in the on-call rotation and take ownership of improving the operational health of the systems you support. Must-haves : 5+ years of experience in data engineering, backend engineering, or a related role; or equivalent experience delivering and operating production data systems. Proven experience independently delivering complex data pipelines or data-platform capabilities from problem definition through production operation. Strong Python and SQL skills, including writing maintainable production code and optimizing non-trivial queries. Hands-on experience with workflow orchestration tools such as Airflow, Prefect, or Dagster. Strong understanding of data modeling, including designing maintainable analytical models and data contracts for multiple consumers. Solid knowledge of data architectures and storage systems, including the trade-offs between different processing and storage approaches. Experience designing for reliability: testing, monitoring, data-quality validation, alerting, debugging, and incident resolution. Ability to make technical decisions under ambiguity, explain trade-offs clearly, and collaborate effectively with engineers and non-technical stakeholder Nice - to - have s : Experience with real-time or event-driven data platforms and streaming technologies. Experience building or operating cloud-native services with Docker and Kubernetes. Familiarity with Infrastructure as Code, particularly Terraform. Experience with data governance, access control, privacy, and compliance requirements such as GDPR or SOC 2. Experience with data observability and quality tools or frameworks, such as Great Expectations. Experience improving engineering standards through shared libraries, platform tooling, technical documentation, or mentoring. We conduct coding interviews as part of the process. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.