Manifold Bio builds AI models for protein therapeutic design, trained on proprietary experimental data generated at unprecedented scale. Our in vivo-centric discovery platform produces millions of experimentally validated protein designs per campaign—creating the datasets that make our models possible and our approach uniquely powerful. We combine high-throughput protein engineering with computational design to create antibody-like drugs and other biologics. Our world-class team of protein engineers, biologists, and computational scientists are working together to aim the platform at therapeutic opportunities where precise targeting is the key to overcoming clinical challenges.
Position
Manifold Bio is seeking an exceptional Machine Learning Scientist to lead research initiatives within our AI team and drive innovation in protein design methodologies. This role will support and enrich the team’s current generative de novo protein design capabilities, as well as break ground on building foundational models on relevant protein therapeutic properties including binding affinity, developability, and in vivo biodistribution and pharmacokinetic (PK) properties. You will be expected to independently conceive, design and execute high-impact research projects that push the boundaries of AI applications in protein design, while contributing to publications and representing Manifold’s scientific contributions to the broader research community.
This is an on-site role and can be based in either Boston, Massachusetts or San Francisco, California. Please only apply if you reside in these cities or are open to relocate.
Responsibilities
Required Qualifications
Preferred Qualifications
This Role Might Be Perfect For You If
You are passionate about leveraging state of the art machine learning approaches to solve challenging disease areas
If you're excited to build scalable ML systems that revolutionize protein therapeutic discovery, please reach out to careers@manifold.bio.
We value different experiences and ways of thinking and believe the most talented teams are built by bringing together people of diverse cultures, genders, and backgrounds.
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