Staff Applied AI Researcher (Agentic Search)
Nebius, Amsterdam, Netherlands +6
What you will do
What you'll work on
- Designing an agent-native search system that handles everything from low-latency single-hop search to complex deep search tasks requiring iterative planning, querying, refinement and reasoning.
- Training ranking and retrieval models optimized for agent-driven workflows under real world constraints
- Bringing the latest advances from the research community to our search stack and ship it to production.
Your responsibilities
- Drive applied research and technical direction across retrieval and ranking systems
- Design and evolve multi-stage retrieval architectures (query understanding, rewriting, retrieval, reranking and iterative retrieval)
- Lead experimentation on modern retrieval approaches (embedding research, sparse and hybrid retrieval, reranking, context compression) and bring them into production
- Develop methods for grounding LLMs in real-time web data at scale, using trust, quality and freshness signals to surface reliable sources