
BigHat Biosciences is a Series B biotech company based outside San Francisco, focused on developing safer and more effective antibody therapies using machine learning and synthetic biology. Their Milliner platform integrates a high-speed wet lab with advanced machine learning technologies for antibody discovery and engineering. With over $100 million raised from top investors, BigHat is positioned to tackle complex therapeutic challenges and has a pipeline of both wholly-owned and partnered programs.

BigHat Biosciences is a Series B biotech company based outside San Francisco, focused on developing safer and more effective antibody therapies using machine learning and synthetic biology. Their Milliner platform integrates a high-speed wet lab with advanced machine learning technologies for antibody discovery and engineering. With over $100 million raised from top investors, BigHat is positioned to tackle complex therapeutic challenges and has a pipeline of both wholly-owned and partnered programs.
Founded: 2019
Headquarters: San Mateo / Bay Area, California
Stage: Series B
Total funding: $75M Series B; ~$100–105M total reported
Platform: Milliner — ML-guided antibody design integrated with a high-throughput wet lab
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Antibody discovery and engineering for therapeutic applications (oncology, inflammation, infectious disease).
2019
Biotechnology Research
$19,000,000
Announced as an oversubscribed Series A
$75,000,000
Participants included Amgen Ventures, Bristol Myers Squibb, Quadrille Capital, Gaingels, GRIDS Capital
“Presence of strategic corporate and top-tier VC investors (Section 32, Andreessen Horowitz, Amgen Ventures, Bristol Myers Squibb, 8VC) and Series B financing”
Department: DS/ML (Data Science/Machine Learning)
Location: San Mateo, CA
Description 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 that 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.
Key Responsibilities
Skills Knowledge And Expertise
Total Rewards The salary estimated for this position is $233,000 - $266,000 + bonus + options + benefits. Compensation will vary depending on job-related knowledge, skills, and experience. Actual compensation will be confirmed in writing at the time of the offer.
What BigHat Offers