Staff / Principal Applied AI Researcher (Agentic Search)

Nebius is leading a new era in cloud infrastructure for the global AI economy. They are seeking a Staff or Principal Applied AI Researcher to join their team in building an agent native search platform designed for AI systems, focusing on innovative retrieval and ranking methods that support real-time data processing.

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