Staff/Principal AI Researcher: Agentic Retrieval & LLM Systems

Nebius Group; Greater London; On-site; GBP 120,000 - 180,000; Full time

Benefits offered by this job

Competitive compensation

Career growth and learning opportunity

Flexibility and ownership

Collaborative and innovative culture

Opportunity to work on impactful AI

International environment and talented

Job summary

Nebius is 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 will own key parts of applied AI research direction, designing systems where AI agents plan, retrieve, evaluate, and refine information in real time at scale.

You will lead the development of retrieval architectures, grounding LLMs in web data, and evaluating agentic workflows under strict latency and reliability constraints.

Qualifications

• 8+ years of experience in applied AI, ML, or software engineering.
• Proven track record shipping ML/AI systems to production at scale.
• Deep experience with search, retrieval, ranking, 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.

Responsibilities

• 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.

Skills

Applied AI/ML experience

Ship ML/AI systems to production

Search, retrieval, ranking, recomm.

Python programming

Go or C++ experience

Fast-moving environment

Job description

Nebius is 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 will own key parts of applied AI research direction, designing systems where AI agents plan, retrieve, evaluate, and refine information in real time at scale.

You will lead the development of retrieval architectures, grounding LLMs in web data, and evaluating agentic workflows under strict latency and reliability constraints.