Staff / Principal Applied AI Researcher (Agentic Search)

Stack

Responsibilities

• ▹Design agent-native retrieval systems optimized for machine consumption rather than human search UX
• ▹Build systems where LLMs iteratively plan, query, refine, and reason over results
• ▹Develop ranking and retrieval approaches for multi-step, agent-driven workflows
• ▹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
• ▹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
• ▹Mentor engineers and help raise the technical bar of the team

Requirements

• ▹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

Soft skills

About the company

Nebius is a full-stack AI cloud platform for the global AI economy, listed on Nasdaq (NBIS) and headquartered in Amsterdam, with a global footprint across Europe, the UK, North America, and Israel, and a team of 1,500+ including hundreds of engineers.