Staff Applied AI Researcher (Agentic Search)
At a glance
Senior AI Research role at Nebius. Remote, Netherlands.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Set research priorities for retrieval and ranking, then shape the technical design behind those systems
- Build multi-stage retrieval flows that interpret queries, rewrite them, rerank results and retrieve iteratively
- Ground language models in live web information and create ways to assess agent systems beyond clicks
- Test embeddings, hybrid search and reranking, then move effective methods into production
- Balance relevance, speed and cost while partnering with engineering to deploy reliable, high-throughput systems
What you bring
- At least eight years in applied AI, machine learning or software engineering
- A record of launching machine-learning or AI systems at production scale
- Strong grounding in search, retrieval, ranking, recommendations or assistants, plus transformers and embeddings
- Experience with LLM-based or knowledge-heavy systems and frameworks for evaluating machine-learning performance
- Strong Python skills and proficiency in Go, C++ or a comparable language
Who this fits
This senior research role suits someone ready to take ownership of unclear problems, influence research and product choices, and mentor engineers. The position is based in London, and applicants must be authorized to work in the country where they apply.
From the employer
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 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.