Staff Applied AI Researcher (Agentic Search)

Tavily

Contract type

Ongoing

Work mode

Remote · Zurich

Experience

Senior · 8+ years

Job description

Staff Applied AI Researcher at Tavily, building an agent-native search platform (the web access layer for AI systems). The role owns applied AI research and system design across retrieval and ranking, shipping measurable impact in production.

At a glance

Work mode: Remote · Zurich

What you'll do

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
Design an agent-native search system handling low-latency single-hop search to complex deep search tasks requiring iterative planning, querying, refinement and reasoning
Train ranking and retrieval models optimized for agent-driven workflows under real world constraints
Bring the latest advances from the research community to the search stack and ship it to production

What we're looking for

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

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About Tavily

Building an agent-native search platform - the web access layer for AI systems, designed for machines rather than humans.

Key facts

Building agentic search where AI systems plan, retrieve, evaluate, and refine information
Systems serve tens of thousands of production workloads 24/7