Senior Applied AI Researcher (Agentic Search)
Role details
Job location
Tech stack
Job description
We are looking for a Senior Applied AI Researcher to work at the intersection of AI research, search quality, and product strategy. In this role, you will explore how modern AI systems and agents should interact with search, and translate those insights into practical improvements in retrieval, ranking, and answering quality. You will work on semantic retrieval, reranking, and evaluation, while also helping shape the long-term direction of the product. This is not a purely academic role. You will be expected to prototype, validate ideas on real systems, and collaborate closely with engineers and product leaders. Over time, you may help guide or mentor more research-focused contributors as the team grows. In this position, your responsibility will be to
- Explore and articulate how AI agents should use search, including new interaction patterns, query formulations, and evaluation criteria beyond traditional keyword relevance
- Conduct deep applied research on search quality, focusing on moving from "textual match" toward answering the underlying question or intent
- Train ranking and reranking models that optimize for answering intent and efficient resolution of agent queries, rather than purely textual similarity.
- Design, prototype, and evaluate ranking and reranking approaches, including neural and LLM-based methods
- Work on semantic retrieval and embedding-based ANN systems, including model selection, adaptation, and tradeoffs between recall, precision, and latency
- Define and evolve quality metrics and evaluation methodologies appropriate for agentic search and question answering
- Collaborate closely with backend and ML engineers to turn research ideas into production-ready components
- Partner with product managers to connect research insights with product strategy and roadmap decisions
- Serve as a technical thought leader for applied AI topics in the team, and help set direction for future research-oriented hires
Requirements
Do you have experience in Keyword research?, Do you have a Master's degree?, * Have experience working on applied ML, NLP, or IR problems in production-facing systems
- Are comfortable moving between conceptual research and hands-on prototyping
- Have worked on or around search, ranking, retrieval, recommendation, or question answering systems
- Understand modern approaches to embeddings, reranking, and LLM-based reasoning, even if you are not training large models from scratch
- Enjoy thinking about product-level questions ("what should the system do?"), not just model internals
- Can communicate complex ideas clearly to engineers, product managers, and non-research stakeholders
- Have the maturity and curiosity to help shape a research direction, not just execute on predefined tasks
Strong candidates may also have experience with:
- LLM-based retrieval, RAG systems, or agentic workflows
- Designing or running offline and online evaluations for search or answer-centric systems
- Bridging industry work with academic research, including reading papers and adapting ideas pragmatically
- Informal technical leadership or mentorship in mixed research/engineering teams
Benefits & conditions
- Competitive salary and comprehensive benefits package.
- Opportunities for professional growth within Nebius.
- Flexible working arrangements.
- A dynamic and collaborative work environment that values initiative and innovation.
We're growing and expanding our products every day. If you're up to the challenge and are excited about AI and ML as much as we are, join us!