Research, ML

Exa; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Premium healthcare benefits

Fertility benefits

16 weeks parental leave

Wellness stipend

Job summary

Exa in San Francisco seeks an ML Research Engineer to train embedding models for perfect web search. You will design transformer-based architectures, build large-scale datasets, and create robust evals to push the state-of-the-art. This role requires a strong ML background and the drive to advance search quality.

Location is in-person in San Francisco, with visa sponsorship for international candidates. Exa offers premium healthcare, fertility benefits, 16 weeks of parental leave, and a monthly

Qualifications

• Graduate-level ML experience required (MS/PhD or exceptional undergrad).
• Ability to implement a transformer from scratch in PyTorch.
• Experience creating large-scale datasets and analyzing them.
• Interest in high quality knowledge for search and information retrieval.

Responsibilities

• Train embedding models for web-scale search.
• Dream up transformer-based architectures for search tasks.
• Create datasets and evaluation protocols to measure progress.
• Beat internal state-of-the-art models and iterate toward better accuracy.

Skills

Graduate-level ML experience

Transformer in PyTorch

Large-scale datasets

Education

Master's or PhD in ML

Tools

PyTorch

Job description

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.

Research at Exa

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.

Desired Experience

• 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

Example Projects

• 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)

Logistics

• 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.