Staff Applied AI Researcher (Agentic Search)

About the Position

Staff Applied AI Researcher (Agentic Search)

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

We are seeking a Staff Applied AI Researcher to join a fast-growing team building an agent-native search platform - the web access layer for AI systems. You can think of this as Google search, but for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results.

Responsibilities

• Designing an agent-native search system that handles everything from low-latency single-hop search to complex deep search tasks requiring iterative planning, querying, refinement, and reasoning.
• Training ranking and retrieval models optimized for agent-driven workflows under real-world constraints.
• Bringing the latest advances from the research community to our search stack and shipping it to production.
• Drive applied research and technical direction across retrieval and ranking systems.
• Design and evolve multi-stage retrieval architectures (query understanding, rewriting, retrieval, reranking, and iterative retrieval).
• Lead experimentation on modern retrieval approaches (embedding research, sparse and hybrid retrieval, reranking, context compression) and bring them into production.
• Develop methods for grounding LLMs in real-time web data at scale, using trust, quality, and freshness signals to surface reliable sources.
• Partner with the evaluation team to define new metrics for agentic systems, where correctness is not reducible to clicks.
• Analyze trade-offs across relevance, latency, and cost, and work closely with engineering to deploy systems that operate at web scale.
• Mentor researchers and 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, or building RAG-based 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.
• Top-tier publications (ICLR, ICML, NeurIPS, AAAI, EMNLP, ACL).
• Ability to operate in a fast-moving, product-driven environment with high ownership and autonomy.

Nice to Have

• Background in agentic AI systems (agents, tool use, autonomous workflows).
• Experience with RL post-training of LLMs or VLMs.

We Offer

• 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.

About the Company

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.

If you need accommodations during the application process, please let us know.

What's it like to work at Nebius:

Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI.