About the role
Nebius is hiring a Staff Applied AI Researcher to shape an agent-native search platform for AI systems. The work centers on retrieval and ranking for agents that plan, query, evaluate, and refine information, with production workloads operating over changing web data under strict latency and reliability constraints.
The role owns research direction and system design across multi-stage retrieval, query rewriting, reranking, real-time grounding, and evaluation methods for agentic systems. The researcher will lead experiments, bring approaches such as embeddings and hybrid search into production, assess relevance, latency, and cost trade-offs, and work closely with engineering teams. Nebius seeks experience shipping ML or AI systems at scale, strong search or retrieval expertise, and depth in transformers, embeddings, and ML evaluation. The role also includes end-to-end ownership of ambiguous problems, contribution to product and research direction, and mentoring engineers.
Highlights
- Shape applied AI research and technical direction for agentic search.
- Design multi-stage retrieval and ranking architectures for LLM workflows.
- Ship and evaluate systems in high-throughput, low-latency environments.
- Mentor engineers and help set the team’s technical bar.
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