Staff Applied AI Researcher (Agentic Search)

Overview

Tavily is seeking a Staff Applied AI Researcher to join its team in London, United Kingdom. The organization is building an agent-native search platform designed as the web access layer for AI systems, functioning as a search system for machines rather than humans. The platform involves agentic search where AI systems actively plan, retrieve, evaluate, and refine information in real time under strict latency and reliability constraints, operating over constantly changing unstructured data and serving production workloads around the clock.

Requirements

Applicants must have at least eight years of experience in applied AI, machine learning, or software engineering, along with a proven track record of shipping machine learning or AI systems to production at scale. Candidates are required to have deep experience with search, retrieval, ranking, or building RAG-based assistants, a strong understanding of modern deep learning with a focus on transformers and embeddings, and experience with LLM-integrated or knowledge-intensive systems. Additional requirements include experience designing evaluation frameworks and metrics for machine learning systems, strong programming skills in Python, top-tier publications at venues such as ICLR, ICML, NeurIPS, AAAI, EMNLP, or ACL, and the ability to operate autonomously in a fast-moving environment. A background in agentic AI systems or reinforcement learning post-training of large language models or vision-language models is considered a nice to have.