Research Engineer
Chai Discovery - San Francisco office, San Francisco, California, United States
Posted Sep 5, 2024
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
State eligibility is not yet verified.
About this role
Research Engineer San Francisco office, San Francisco, California, United States 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 seeking an AI Research Engineer to help design, train, evaluate, and optimize Chai's core models and infrastructure, working in tight loops with research scientists. Chai's models are moving beyond protein structure prediction into real-world therapeutic engineering. This is a chance to push the frontier of AI drug design, working alongside a craft-obsessed team of micro-pessimists and macro-optimists. - Develop and optimize all the infrastructure & tooling upon which our AI research depends. - Collaborate with AI researchers to understand, implement and optimize new research directions. - Integrate AI models into production systems, ensuring scalability and reliability. About you Ideal backgrounds include high-performance computing, custom CUDA kernels and GPU programming, AI/ML + data systems at scale. - Bachelor's or Master's degree in Computer Science, Software Engineering,
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