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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 team The Hardware Automation team builds the internal platforms and tooling that power how Nebius operates its data center infrastructure at scale. Our mission is to eliminate manual effort, reduce human error, and give every team in the Hardware Infrastructure department real-time visibility and control over the systems they own. We operate as a product engineering team embedded within hardware infrastructure — meaning we don't just write requirements and hand them off. We own the full stack: from requirements gathering with data center operations and hardware engineering, through design and build, all the way to rollout and ongoing reliability. The Role Nebius is looking for a Senior Software Engineer to join the Hardware Infrastructure Observability team. You're welcome to work from our office in Amsterdam. We build and run low-level monitoring for servers and data center engineering systems to ensure reliability at scale. We also design and operate maintenance and remediation systems that enable safe, predictable fleet-wide changes and keep the infrastructure healthy. Key Responsibilities: Design and develop services and agents that provide deep visibility into a large server fleet and DC engineering systems Evolve our metrics/aggregation/alerting pipelines and improve signals quality Build maintenance workflows and automation that keep fleets healthy Investigate incidents hands-on (including on-host debugging) and drive root-cause fixes Collaborate with hardware, networking, and DC operations to improve reliability We expect you to have: 5+ years of professional software engineering experience Excellent knowledge of Python and Golang or you are ready to quickly switch to these programming languages Strong Linux fundamentals Ability to write reliable code and and dig into complex problems Working proficiency in English We expect Engineers to: Manage large-scale projects involving multiple stakeholders Break down complex tasks and guide both their own work and that of more junior colleagues Be experts in specific technologies and write high-quality code that can serve as a reference Assess task priority and focus on high-impact work, avoiding low-value efforts Have strong architectural thinking and contribute to system design Be involved in hiring and actively contribute to interviews Be willing to share knowledge and mentor others It will be an added bonus if you have: Solid understanding of modern server architecture, and its components Experience with metrics/monitoring/alerting Prometheus-compatible stacks (like VictoriaMetrics) Good knowledge of computer networks Experience designing, developing, and running high-load distributed systems Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and ownership Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The Role We’re looking for a Software Engineer to build software that makes network operations safe, scalable, and boring — even as we launch new data centers and expand fast. This is not a “write scripts for configs” role: you’ll build the tooling and services that sit between the network core (switches/ports/VLANs, traffic processors) and the cloud platform on top, using open source where it fits and building the missing pieces where it doesn’t. Your responsibilities will include: Build and maintain services and tooling that automate the network lifecycle: day-0 provisioning, day-N changes, drift detection, and operational verification Make network changes safe and transparent: CI/CD workflows, diff/review tooling, staged rollouts/rollbacks, audit trails, and guardrails Develop observability systems that scale across many sites: telemetry pipelines, signal quality, and tooling that shortens incident investigations Close “last mile” gaps between the network and the platform: integrate source-of-truth data, expose APIs, and build reliable automation around it Collaborate closely with network engineers and SREs to turn real operational pain into product-quality tooling We expect you to have: 5+ years of professional software engineering experience (or equivalent practical background) Strong coding skills and ownership mindset: you can ship and operate reliable services Proficiency in Go or readiness to switch; Python is also welcome (other languages can be useful for OSS debugging/fixes) You don’t have to be Network expert but we expect you to have interest in infrastructure and/or network It will be an added bonus if you have: Background in networking (ex-network engineer, CCNP/education, DC networking exposure) or strong interest and proven ability to learn fast Experience building automation/infra tooling: CI/CD, IaC, testing/staging environments, or “network-as-code” style workflows Low-level networking / datapath experience: eBPF/XDP, DPDK, kernel networking, traffic processing systems Experience designing high-load services and observability platforms (metrics/logs/traces, alerting, regression detection) Contributions to open source or experience extending/debugging OSS components in production environments We expect Engineers to: Manage large-scale projects involving multiple stakeholders Break down complex tasks and guide both their own work and that of more junior colleagues Be experts in specific technologies and write high-quality code that can serve as a reference Assess task priority and focus on high-impact work, avoiding low-value efforts Have strong architectural thinking and contribute to system design Be involved in hiring and actively contribute to interviews Be willing to share knowledge and mentor others 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’re looking for a Software Engineer to build software that makes network operations safe, scalable, and boring — even as we launch new data centers and expand fast. This is not a “write scripts for configs” role: you’ll build the tooling and services that sit between the network core (switches/ports/VLANs, traffic processors) and the cloud platform on top, using open source where it fits and building the missing pieces where it doesn’t. Your responsibilities will include: Build and maintain services and tooling that automate the network lifecycle: day-0 provisioning, day-N changes, drift detection, and operational verification Make network changes safe and transparent: CI/CD workflows, diff/review tooling, staged rollouts/rollbacks, audit trails, and guardrails Develop observability systems that scale across many sites: telemetry pipelines, signal quality, and tooling that shortens incident investigations Close “last mile” gaps between the network and the platform: integrate source-of-truth data, expose APIs, and build reliable automation around it Collaborate closely with network engineers and SREs to turn real operational pain into product-quality tooling We expect you to have: 5+ years of professional software engineering experience (or equivalent practical background) Strong coding skills and ownership mindset: you can ship and operate reliable services Proficiency in Go or readiness to switch; Python is also welcome (other languages can be useful for OSS debugging/fixes) You don’t have to be Network expert but we expect you to have interest in infrastructure and/or network It will be an added bonus if you have: Background in networking (ex-network engineer, CCNP/education, DC networking exposure) or strong interest and proven ability to learn fast Experience building automation/infra tooling: CI/CD, IaC, testing/staging environments, or “network-as-code” style workflows Low-level networking / datapath experience: eBPF/XDP, DPDK, kernel networking, traffic processing systems Experience designing high-load services and observability platforms (metrics/logs/traces, alerting, regression detection) Contributions to open source or experience extending/debugging OSS components in production environments We expect Engineers to: Manage large-scale projects involving multiple stakeholders Break down complex tasks and guide both their own work and that of more junior colleagues Be experts in specific technologies and write high-quality code that can serve as a reference Assess task priority and focus on high-impact work, avoiding low-value efforts Have strong architectural thinking and contribute to system design Be involved in hiring and actively contribute to interviews Be willing to share knowledge and mentor others 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 Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact 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 Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact 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 Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact 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 Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact 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 Staff or Principal Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. You can think of this as Google for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines. We are designing how AI agents - not humans - retrieve, evaluate, and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval and ranking under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24 by 7. This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. What you'll work on: Designing agent native retrieval systems optimised for machine consumption rather than human search UX Building systems where LLMs iteratively plan, query, refine, and reason over results Developing ranking and retrieval approaches for multi step, agent driven workflows under real world constraints Your responsibilites: Drive applied research and technical direction across retrieval and ranking systems Design and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) Develop methods for grounding LLMs in real time web data at scale Define and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks Lead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production Analyse trade-offs across relevance, latency, and cost at scale Work closely with engineering to deploy systems in high throughput, low latency environments Own ambiguous problems end to end and contribute to product and research direction Mentor engineers and help raise the technical bar of the team Must haves: 8+ years of experience in applied AI, ML, or software engineering Proven track record of shipping ML or AI systems to production at scale Deep experience with search, retrieval, ranking, recommendation systems, or assistants Strong understanding of modern deep learning, especially transformers and embeddings Experience with LLM integrated or knowledge intensive systems Experience designing evaluation frameworks and metrics for ML systems Strong programming skills in Python and at least one of Go, C++, or similar Ability to operate in a fast moving, product driven environment with high ownership and autonomy Nice to haves Experience with large scale search or recommendation systems Background in agentic AI systems (agents, tool use, autonomous workflows) Experience with RAG, multi step retrieval, or tool use Publications, open source, or similar signals of technical depth and impact 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.