Staff Applied AI Researcher (Agentic Search)

h3About Nebius /h3 pNebius 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. /p pBuilt by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. /p pListed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with RD 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 RD. /p pWe are seeking a Staff Applied AI Researcher to join a fast growing team building an agent native search platform - the web access layer for AI systems. /p pYou 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. /p pWe 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. /p pThis 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. /p h3What You'll Work On /h3 ulliDesigning agent native retrieval systems optimised for machine consumption rather than human search UX /liliBuilding systems where LLMs iteratively plan, query, refine, and reason over results /liliDeveloping ranking and retrieval approaches for multi step, agent driven workflows under real world constraints /li /ul h3Your Responsibilites /h3 ulliDrive applied research and technical direction across retrieval and ranking systems /liliDesign and evolve multi stage retrieval architectures (query understanding, rewriting, reranking, iterative retrieval) /liliDevelop methods for grounding LLMs in real time web data at scale /liliDefine and implement new evaluation paradigms and metrics for agentic systems, where correctness is not reducible to clicks /liliLead experimentation on modern retrieval approaches (embeddings, hybrid search, reranking) and bring them into production /liliAnalyse trade-offs across relevance, latency, and cost at scale /liliWork closely with engineering to deploy systems in high throughput, low latency environments /liliOwn ambiguous problems end to end and contribute to product and research direction /liliMentor engineers and help raise the technical bar of the team /li /ul h3Must Haves /h3 ulli8+ years of experience in applied AI, ML, or software engineering /liliProven track record of shipping ML or AI systems to production at scale /liliDeep experience with search, retrieval, ranking, recommendation systems, or assistants /liliStrong understanding of modern deep learning, especially transformers and embeddings /liliExperience with LLM integrated or knowledge intensive systems /liliExperience designing evaluation frameworks and metrics for ML systems /liliStrong programming skills in Python and at least one of Go, C++, or similar /liliAbility to operate in a fast moving, product driven environment with high ownership and autonomy /li /ul h3Nice to haves /h3 ulliExperience with large scale search or recommendation systems /liliBackground in agentic AI systems (agents, tool use, autonomous workflows) /liliExperience with RAG, multi step retrieval, or tool use /liliPublications, open source, or similar signals of technical depth and impact /li /ul h3Benefits Perks /h3 ulliCompetitive compensation /liliCareer growth and learning opportunities /liliFlexibility and ownership /liliCollaborative and innovative culture /liliOpportunity to work on impactful AI projects /liliInternational environment and talented teams /li /ul h3What's It Like To Work At Nebius /h3 pFast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI /p h3Equal Opportunity Statement /h3 pNebius 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. /p pApplicants 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. /p pIf you need accommodations during the application process, please let us know. /p #J-18808-Ljbffr