ML Engineer: Antibody Design & Drug Discovery

BigHat; San Mateo, Northern (CA, KY); Hybrid; USD 150,000 - 200,000; Full time

Benefits offered by this job

Bonus

Stock options

Benefits

Job summary

BigHat Biosciences is seeking a Machine Learning Engineer to advance ML-driven antibody design. You will build generative models for antibody sequences and structures, and create multi-objective optimization methods for rapid lab-in-the-loop validation.

Join a fast-paced, interdisciplinary team applying state-of-the-art ML to accelerate therapeutics development, with collaboration across data science, biology, and automation in San Mateo, CA.

Qualifications

• Masters in ML/CS/EE or equivalent.
• Bachelors with 3+ years industry experience.
• Strong quantitative background and hands-on ML methods.
• Excellent communication with diverse teams.
• Familiarity with ML-driven protein engineering.
• Nice-to-haves: de novo design, NGS data, Bayesian optimization, AWS, publications.

Responsibilities

• Design state-of-the-art generative models of antibody sequence/structure and predictive models on proprietary datasets.
• Develop multi-modality, multi-objective protein sequence optimization for lab-in-the-loop design in high-throughput lab.
• Develop and deploy agentic and LLM-driven optimization methods to accelerate the design-build-test loop.
• Provide ML expertise to ongoing therapeutics programs and contribute to drug development.
• Collaborate with engineering to ensure efficient deployment of models and methods.
• Work with interdisciplinary teams across drug development and wet labs.

Skills

Python

PyTorch

Software engineering

Communication

Biomedical knowledge

Protein engineering ML

Publications

NGS data

Bayesian optimization

De novo design

Education

Masters in ML/CS/EE

Bachelors + 3+ years

Tools

AWS

CI/CD

Git

Job description

BigHat Biosciences is seeking a Machine Learning Engineer to advance ML-driven antibody design. You will build generative models for antibody sequences and structures, and create multi-objective optimization methods for rapid lab-in-the-loop validation.

Join a fast-paced, interdisciplinary team applying state-of-the-art ML to accelerate therapeutics development, with collaboration across data science, biology, and automation in San Mateo, CA.