Staff Applied AI Researcher — Agentic Search & Retrieval

Tavily; Zürich; Híbrido; CHF 180.000 - 240.000; Jornada completa

Descripción de la vacante

Tavily is seeking a Staff Applied AI Researcher to help build an agent-native search platform, the web-access layer for AI systems. This role focuses on ownership of key parts of the applied AI research direction with measurable production impact, starting with a specific part of the search stack such as ranking or iterative retrieval.

You'll design an agent-native search system, train ranking and retrieval models, and bring cutting-edge research from the community to production, while solving

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Applied AI

ML Systems

Search & Retrieval

Transformers

LLMs

Python

Experimentation

Descripción del empleo

Tavily is seeking a Staff Applied AI Researcher to help build an agent-native search platform, the web-access layer for AI systems. This role focuses on ownership of key parts of the applied AI research direction with measurable production impact, starting with a specific part of the search stack such as ranking or iterative retrieval.

You'll design an agent-native search system, train ranking and retrieval models, and bring cutting-edge research from the community to production, while solving