Staff / Principal Applied AI Researcher (Agentic Search)
Nebius — Zurich, Zurich, Switzerland · In-Person · Staff+
Role description
Role Overview
Join a fast-growing team building an agent native search platform, designing systems for machines to retrieve, evaluate, and reason over web data in real-time under strict latency and reliability constraints.
What You Will Do
Design agent native retrieval systems, build systems where LLMs iteratively plan, query, refine, and reason over results, develop ranking and retrieval approaches for multi-step, agent-driven workflows.
Why It Might Be a Fit
Drive applied research and technical direction, design and evolve multi-stage retrieval architectures, develop methods for grounding LLMs in real-time web data at scale, define and implement new evaluation paradigms and metrics.
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 in Python and at least one of Go, C++, or similar
- Ability to operate in a fast-moving, product-driven environment with high ownership and autonomy
Benefits
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams