1. BigHat Biosciences
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  3. Principal, Machine Learning Scientist
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Role description

Principal, Machine Learning Scientist

BigHat Biosciences logoBigHat Biosciences
AI-native
WorkplaceOn-site
SeniorityPrincipal
Location

Company info

BigHat Biosciences logo

BigHat Biosciences

BigHat Biosciences is a novel protein therapeutics company and developer of an AI-guided antibody design platform

BigHat’s mission is to improve human health by making it far easier to design advanced, next-generation antibody therapeutics. Our AI-enabled experimental platform integrates a high-speed characterization or “wet” lab with machine learning technologies to speed the antibody engineering process. When applied, these design capabilities have the potential to drive the development of new generations of safer and more effective treatments for patients suffering from today’s most challenging diseases. BigHat is backed by Section 32, ‍Andreessen Horowitz, 8VC, Amgen Ventures, Bristol Myers Squibb, Quadrille, Grids Capital, AME Cloud Ventures, Innovation Endeavors and Gaingels.

Private companySeries CRecently raised
Founded2019
HQSan Mateo, United States
San Mateo, CA
Research

The role: We are seeking a creative, accomplished Principal Machine Learning Scientist to advance the state of the art in ML-driven therapeutic antibody design.

At BigHat Biosciences our full-stack antibody drug development platform uses ML to drive every stage from discovery to optimization. Our roboticized high-throughput wet-lab continually adds to our large proprietary datasets, which are piped through a custom LIMS++ data management and orchestration layer to automatically update and deploy the latest models. This makes the development of complex, next-gen therapeutics ‘trivially parallelizable’, at a pace which only accelerates as we develop better ML tooling.

You’re not interested in just git-cloning the latest NeurIPS pub and swapping out the dataset. Motivated by an enthusiasm for the possibility of addressing unmet patient needs and a curiosity about the underlying biology, you’ll apply your world-class ML skillset to refine and expand this state-of-the-art protein engineering platform. Success will mean not only hands-on methods development, but helping shape the direction for future ML research, and actively participating in the application of our platform to the accelerated design of new therapeutics.

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Size
51-200 employees
IndustryBiotechnology Research
Latest fundingSeries C · Sep 24, 2026
Investors
8VCInnovation EndeavorsAME Cloud VenturesAndreessen Horowitz
Tech stackprism, tableau, amazon-ecs, broadly, workspace, microsoft-powerpoint, pytorch, jira, graphpad-prism, zoom, agilent, google-docs, runcode, google-cloud-platform, netsuite, postgresql, zoom-rooms, benchmark, microsoft-typescript, pandas

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