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Exa is an applied AI lab building a next-generation search engine powered by massive-scale infrastructure, state-of-the-art embedding models, and high-performance vector databases. The company powers search for Cursor, Cognition, HubSpot, and over 400,000 developers, with $350M in funding from Lightspeed, Benchmark, and a16z.
The ML Research Engineer role sits at the heart of Exa's mission to build perfect search over all the world's information. You will train foundational embedding models designed to instantly filter the world's knowledge to match complex queries, essentially putting the web into an extremely powerful database.
Key responsibilities include:
- Designing and implementing novel transformer-based search architectures
- Creating large-scale datasets for training and evaluation
- Building evaluation systems to measure search quality improvements
- Training and fine-tuning models at scale (hundred-billion parameter range)
- Implementing RLAIF pipelines and other advanced training methodologies
- Iterating rapidly to beat internal state-of-the-art benchmarks
You will work on projects spanning pre-training massive models, fine-tuning for specific search tasks, architecting novel approaches to search problems, and developing rigorous evaluation frameworks to answer the critical question: how do we know we're advancing search quality?
The role requires deep expertise in machine learning, strong PyTorch skills, and the ability to code transformer architectures from scratch. You should be comfortable working with large-scale datasets, diving deeply into data quality issues, and have graduate-level ML experience or exceptional undergraduate credentials. The ideal candidate is passionate about the problem of finding high-quality knowledge and recognizes its importance for the world.
Exa sponsors international visas and has a strong track record of successfully bringing talent from around the world. The company offers premium healthcare (medical, dental, vision), fertility benefits, 16 weeks fully paid parental leave, and monthly wellness stipends.
