
BigHat Biosciences builds an AI-enabled experimental platform that designs and optimizes antibody therapeutics to improve safety and efficacy. Its Milliner platform integrates a high-speed wet lab…

BigHat Biosciences builds an AI-enabled experimental platform that designs and optimizes antibody therapeutics to improve safety and efficacy. Its Milliner platform integrates a high-speed wet lab…
Founded: 2019
Headquarters region: San Mateo / San Carlos, CA area
Core focus: AI-driven antibody discovery and engineering
Tech/Platform: Milliner platform combining ML, synthetic biology, and high-speed wet lab
Latest disclosed round: Series B $75M (Jul 20, 2022)
Notable investors: Section 32, Andreessen Horowitz, Amgen Ventures, Bristol-Myers Squibb, 8VC
Antibody therapeutics discovery and engineering
2019
Biotechnology Research
$5M (approximate)
Seed financing reported as approximately $5 million
$19M
Oversubscribed Series A
$75M
Series B participation included Amgen Ventures, Bristol Myers Squibb, Quadrille Capital, Gaingels, and others
“Company has participation from strategic biopharma investors and large venture firms (e.g., Section 32, Amgen Ventures, Bristol-Myers Squibb, Andreessen Horowitz)”
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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
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