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Research Engineer - Auto Research

On-site
Chai DiscoverySan Francisco, CA, US1 day agoWebsite
Fresh
Full-time
Research

Compensation

Salary undisclosed
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Description

About Chai Discovery

Chai builds the design suite for molecules. We train frontier models that learn the underlying foundations of biochemical structure and interaction, so scientists can move faster and pursue targets that other methods cannot reach.

AI is reinventing life sciences the same way it reinvented software engineering, and Chai is at the forefront of this shift. Leading pharmaceutical companies like Eli Lilly, Pfizer, and Novartis are adopting our platform to power their drug discovery programs.

We value diverse perspectives and are ready to find greatness in unexpected places.

About the role

Research Engineers on Auto-Research build the agent-powered systems and frameworks that let our research organization move faster — automating parts of the research loop itself rather than just the models it produces. As a Research Engineer on this team, you will:

  • Develop and optimize our agent-powered auto-research framework, improving model training velocity and accelerating inference and iteration cycles.

  • Build the tooling, datasets, and workflows that let agents (and researchers) run experiments, evaluate results, and propose next steps with minimal manual overhead.

  • Automate real research workflows across the model lifecycle - training, evaluation, and deployment - to increase researcher throughput.

About you

  • 4+ years of industry experience working closely with or within AI/ML research teams.

  • Proficiency in Python and familiarity with PyTorch or JAX.

  • Strong software system design skills, particularly around building tools and abstractions that other researchers or agents will build on top of.

  • Experience building agent-powered software systems.

We offer

The opportunity to work at the vanguard of AI research and frontier biology, with world-class people, on a mission that matters. We protect & promote a culture of high velocity and ownership. We compensate our team accordingly.

Stack

PythonPyTorchMachine LearningJAX
Posted
Sep 24, 2026
Last seen
Sep 25, 2026
First seen
Sep 25, 2026

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