Staff Applied AI Researcher (Agentic Search)

<p>&nbsp;</p> <p data-renderer-start-pos="758" data-local-id="349f5d1d97ae">We are seeking a Staff Applied AI Researcher to join a fast-growing team building an agent-native search platform - the web access layer for AI systems.</p> <p data-renderer-start-pos="912" data-local-id="52da8de25c65">You can think of this as Google search, but for AI agents: a system designed for machines, not humans. We are building agentic search, where AI systems actively plan, retrieve, evaluate, and refine information rather than simply returning results. As AI becomes the primary interface to the web, this layer will replace the role of traditional search engines.</p> <p data-renderer-start-pos="1273" data-local-id="8ba2f733eb98">We are designing these systems to search and reason over web data in real time, under strict latency and reliability constraints. This means solving retrieval, ranking and passage extraction under entirely new access patterns and at significant scale, with systems operating over constantly changing, unstructured data and serving tens of thousands of production workloads 24/7.</p> <p data-renderer-start-pos="1653" data-local-id="dc8aefa0b2c5">This role comes with ownership over key parts of our applied AI research direction and system design, with a strong expectation of defining new approaches and shipping measurable impact in production. In the first year, you will own a specific part of the search stack, e.g. ranking or iterative retrieval.</p> <p data-renderer-start-pos="1961" data-local-id="3a68defafc73"><strong data-renderer-mark="true">What you'll work on:</strong></p> <ul class="ak-ul" data-local-id="b2d49ed7-2072-4623-afb5-0f3e46fb9eff" data-indent-level="1"> <li> <p data-renderer-start-pos="1985" data-local-id="dbde4a36f318">Designing an agent-native search system that handles everything from low-latency single-hop search to complex deep search tasks requiring iterative planning, querying, refinement and reasoning.</p> </li> <li> <p data-renderer-start-pos="2182" data-local-id="330562c2b43d">Training ranking and retrieval models optimized for agent-driven workflows under real world constraints</p> </li> <li> <p data-renderer-start-pos="2289" data-local-id="a80b20c7f5e2">Bringing the latest advances from the research community to our search stack and ship it to production.</p> </li> </ul> <p data-renderer-start-pos="2396" data-local-id="c5f3d6d01f8e"><strong data-renderer-mark="true">Your responsibilities:</strong></p> <ul class="ak-ul" data-local-id="ca556365-56d6-4b18-a6ab-e96d32aada2a&quo