Research, ML

The ML organization sits at the heart of our mission. We train foundational models for search. Our goal is to build systems that can instantly filter the world's knowledge to exactly what you want, no matter how complex your query. Basically, put the web into an extremely powerful database.

We're looking for an ML Research Engineer to train embedding models for perfect search over the web. The role involves dreaming up novel transformer-based search architectures, creating datasets, creating evals, beating our internal SoTA, and repeat.

You have graduate-level ML experience (Master's degree or PhD with at least 2 years of relevant experience, or are an exceptionally strong undergrad)

You can code up a transformer from scratch in PyTorch

You like creating large-scale datasets and diving deeply into the data

You care about the problem of finding high quality knowledge and recognize how important this is for the world

Pre-training: Train a hundred billion parameter model

Fine-tuning: Build an RLAIF pipeline for search

Dream up a novel architecture for search in the shower, then code it up and beat our best model's top score

Build an eval system that answers: How do we know we're advancing our search quality? (this is an incredibly difficult question to answer)

Location: This is an in-person opportunity in San Francisco.

Visas: We're happy to sponsor international candidates (e.g., STEM OPT, OPT, H1B, O1, E3). 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.

Exa is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, age, veteran status, marital status, pregnancy or related conditions, criminal histories consistent with applicable law, or any other basis protected by applicable law.