Senior Applied AI Researcher (Agentic Search)

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.