Exa is an applied AI lab building a search engine unlike the world has ever seen. We build massive-scale infra to crawl the entire web, train state-of-the-art embedding models to process it, and design super high performant vector databases to retrieve over it. We now power search for Cursor, Cognition, HubSpot, and over 400,000 developers and have raised $350m from Lightspeed, Benchmark, and a16z.
Our ultimate goal is to build perfect search over all the world's information, far beyond Google. If you want to build massive-scale ML systems that will define the way the new AI world consumes information, this is the place for you.
Generalist Research Engineers work across our search and retrieval stack: crawling, parsing, ML performance, retrieval algorithms. The team is centered around improving end quality of search endpoints for customers.
Desired Experience
High attention to detail; simultaneously understand customer needs and implementation details of the system
Great intellectual horsepower - generalists who are eager to go deep
You're excited to work across our search and retrieval stack: crawling, parsing, ML performance, retrieval algorithms and more
Comfortable working across different systems, and shipping fast
You care about the problem of finding high quality information and recognize how important this is for the world
Example Projects
Design and ship a new parser that dramatically improves retrieval performance
Improve throughput and latency of ML models
Make our web crawler 3x faster
Location: This is an in-person opportunity in Singapore.
Visas: We’re happy to sponsor international candidates! While we cannot guarantee your visa, we have historically been successful in sponsoring candidates from all over the world. If you receive an offer, our team will work hard to get you a visa.
Benefits: We offer premium healthcare benefits (medical, dental, vision), fertility benefits, 16 weeks of fully paid parental leave for all new parents, and a monthly wellness stipend to all of our employees.
Skills Required
- High attention to detail
- Ability to understand customer needs
- Eager to work across various systems
- Excitement about finding high-quality information
What We Do
Exa was built with a simple goal — to organize all knowledge. After several years of heads-down research, we developed novel representation learning techniques and crawling infrastructure so that LLMs can intelligently find relevant information.
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