Machine Learning Engineer
BigHat Biosciences6 days ago
San Mateo, CA, USAMid Level
Base Salary
$150k - $200k/yr
Responsibilities
- Design and implement generative models for antibody sequence and structure and predictive models of antibody properties.
- Develop multi-modality, multi-objective protein sequence optimization methods for lab-in-the-loop antibody design and high-throughput wet-lab validation.
- Develop and deploy agentic and LLM-driven optimization methods to automate and accelerate the design-build-test loop.
- Provide machine learning expertise for therapeutics programs and contribute to new drug development.
- Collaborate with engineering teams to efficiently deploy models and methods.
- Work with interdisciplinary teams spanning drug development, wet-lab science, automation, and data science.
Requirements
- Master's degree in ML, CS, or EE, or a bachelor's degree with 3+ years of industry experience.
- Hands-on experience developing and applying novel machine learning methods and a strong quantitative background.
- Strong Python skills and familiarity with PyTorch.
- Experience with modern software engineering best practices, including testing and CI/CD.
- Sufficient biomedical domain knowledge to collaborate with diverse scientific teams.
- Familiarity with the state of the art in ML-driven protein engineering.
- Preferred experience includes de novo design, NGS data, Bayesian optimization, antibody biology, drug development, AWS model training and deployment, and publications at major ML conferences.
Benefits
- Bonus, options, and benefits are included in the total rewards package.
Categories
About BigHat Biosciences
BigHat Biosciences builds an AI-enabled, high-throughput wet-lab platform to design and optimize antibody therapeutics for biotech and pharma R&D teams. The privately held company develops internal drug programs and collaborates with partners, using machine learning, robotics, and proprietary datasets to accelerate discovery-to-optimization workflows. Founded in 2019 and headquartered in San Mateo, California, it focuses on next-generation biologics for difficult diseases.