Staff Applied AI Researcher - Agent-Native Search Architect

Tavily; Greater London; In loco; GBP 120.000 - 180.000; Tempo pieno

Descrizione del lavoro

Tavily is seeking a Staff Applied AI Researcher to help build an agent-native search platform, a web-access layer for AI systems. You’ll design and own parts of the search stack, focusing on ranking or iterative retrieval in the first year.

You will push forward state-of-the-art retrieval, grounding LLMs in real-time web data, and define evaluation metrics for agentic systems while guiding teams toward scalable, low-latency production solutions.

Competenze

• 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.

Mansioni

• 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.

Conoscenze

Applied AI

Search systems

Python

LLMs

RAG-based

Transformers

Descrizione del lavoro

Tavily is seeking a Staff Applied AI Researcher to help build an agent-native search platform, a web-access layer for AI systems. You’ll design and own parts of the search stack, focusing on ranking or iterative retrieval in the first year.

You will push forward state-of-the-art retrieval, grounding LLMs in real-time web data, and define evaluation metrics for agentic systems while guiding teams toward scalable, low-latency production solutions.