Chai Discovery

Biotech

DataGeneration

$175–250k ~AI est. San Francisco, California, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Data Generation at Chai Discovery”

Industry & Context.

Biotech
Full Job Description

ABOUT CHAI DISCOVERY Chai is a research lab working on AI to unlock biology. Our models design new molecules for new medicines. We are changing how biologists develop drugs, just as language models are changing how engineers write code. Our vision is a design suite for molecules, with applications across life sciences, agriculture, materials and beyond. Our founders have been at the forefront of this field from the beginning. We are backed by Thrive, General Catalyst, OpenAI, Dimension and other tier-one investors. We partner with global life sciences companies like Eli Lilly on deals that are transforming industry. We are known for talent density, rigorous research and pace of execution. ABOUT THE ROLE We are looking for an expert in data operations, or a fast-rising generalist, to take the reins of data generation here at Chai. Someone who operates with urgency, has strong communication and project management skills, and who has an analytical nature. Data is vital to training frontier AI models, testing research hypotheses, and supporting our partners. You will set the vision and execute scaling of Chai’s lab-in-the-loop data platform and drive CRO/external research partners, while working hand-in-hand with our science and research teams. This is a chance to push the boundaries of drug discovery and contribute to some of most advanced AI models ever imagined. Immerse yourself in technologies that represent the future of biotech, and position yourself at the forefront of this emerging field. ABOUT YOU Our ideal candidate can: - Design & drive complex projects and workflows, across multi-party relationships. - Translate scientific goals into concrete, vendor-friendly instructions—assays, deliverables, success criteria, SOWs, timelines, sample trackers, etc. - Juggle concurrent projects and priorities, adapting quickly and keeping everyone in sync. - Communicate highly technical information with clarity. - Define a vision for how we scale data generation efforts by o

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