12 months ago
Base Salary
$150k - $300k/yr
Responsibilities
- Define a vision for perfect search and investigate evaluation approaches for search engines in an LLM world.
- Design and implement evaluation frameworks that probe the limits of search.
- Build scalable, reliable evaluation pipelines tracking regressions, drift, and quality signals across billions of documents.
- Create golden datasets, synthetic benchmarks, agentic tasks, and real-world test suites for developers, agents, and humans.
- Partner with ML researchers, data engineers, infrastructure engineers, and product teams to improve search-model feedback loops.
Requirements
- Hands-on machine learning experience training, fine-tuning, or evaluating models, ideally involving embeddings or LLMs.
- Strong engineering fundamentals and the ability to build reliable systems.
- Experience with Python, Rust, distributed pipelines, and GPU or cluster jobs.
- Enjoys building evaluation sets, inspecting edge cases, and designing creative measurement strategies.
Benefits
- In-person role in San Francisco.
- International candidate sponsorship is available, including STEM OPT, OPT, H1B, O1, and E3.
- Premium medical, dental, and vision healthcare benefits.
- Fertility benefits.
- Monthly wellness stipend.
Categories
About Exa
Exa builds a web-scale search engine and API for AI agents and developer applications, combining its own crawler, embedding models, and high-performance vector search. It sells usage-based APIs and enterprise integrations that power retrieval-augmented generation, browsing, and automation on live web content. The company runs large crawling infrastructure and dedicated GPU clusters to continuously index and embed pages, and ships low-latency search components written in Rust.