Senior Applied AI Researcher (Agentic Search) at Nebius

Nebius is a Nasdaq-listed AI infrastructure provider headquartered in Amsterdam with ~1,400 employees including ~400 engineers. The company recently acquired Tavily, a leading agentic search provider, to expand its integrated software stack for enterprise-grade agentic systems. Position: Senior Applied AI Researcher (Agentic Search) Locations: Amsterdam, Netherlands; Israel; Remote - Europe; United Kingdom Last updated: March 30, 2026 This role focuses on building an agent-native search platform designed for AI systems. You will research how modern AI agents should interact with search capabilities and translate those insights into practical improvements. Key Responsibilities: - Explore interaction patterns between AI agents and search systems, including new query formulations and evaluation methods - Conduct applied research on search quality, moving beyond textual match toward answering underlying intent - Train ranking and reranking models optimizing for agent query resolution - Design and evaluate ranking approaches using neural and LLM-based methods - Work on semantic retrieval and embedding-based systems - Define quality metrics and evaluation methodologies for agentic search - Collaborate with engineers and product managers to transition research into production components - Provide technical leadership and shape research direction Essential Experience: - Applied ML/NLP/IR work in production systems - Comfort moving between conceptual research and hands-on prototyping - Background with search, ranking, retrieval, or question answering systems - Understanding of modern embeddings, reranking, and LLM-based reasoning - Product-level thinking alongside technical depth - Clear communication with diverse stakeholders Preferred Skills: - LLM-based retrieval, RAG systems, or agentic workflows - Offline and online evaluation design for search/answer systems - Bridging academic research with industry applications - Technical leadership in mixed research/engineering teams Tech Stack: LLMs, NLP, RAG, Embedding systems, ANN (Approximate Nearest Neighbor), Neural ranking models Benefits: Competitive salary, professional growth opportunities, flexible arrangements, and collaborative environment.