ML Engineer: Generative Antibody Design & Lab-In-Loop

BigHat Biosciences; San Mateo (CA); On-site; USD 150,000 - 200,000; Full time

Benefits offered by this job

Bonus

Stock options

Benefits

Job summary

BigHat Biosciences in San Mateo, CA, seeks a creative ML Scientist or Engineer to advance ML-driven antibody design across discovery to optimization. Our platform uses AI/ML with large proprietary datasets and automated data management to accelerate drug development.

You will apply top-tier ML to refine our protein engineering stack and contribute to turning platforms into real drug candidates. The role involves building state-of-the-art models, multi-objective optimization, LLM-assisted

Qualifications

• Master's in ML/CS/EE or a BS with 3+ years industry experience.
• Hands-on experience developing novel ML methods.
• Strong Python and PyTorch skills with modern software practices.
• Excellent communication and biomedical domain knowledge.
• Interest in applying ML to protein engineering and drug design.

Responsibilities

• Design and implement state-of-the-art generative models of antibody sequence and structure.
• Develop multi-modality, multi-objective iterative protein sequence optimization approaches for lab-in-the-loop design.
• Develop, refine, and deploy agentic and LLM-driven optimization methods for design-build-test loops.
• Provide ML expertise and support for ongoing therapeutics programs.
• Collaborate with engineering to ensure efficient deployment of models and methods.
• Work with interdisciplinary teams of drug developers, wet lab scientists, and data scientists.

Skills

ML/CS/EE fundamentals

Python

PyTorch familiarity

Communication skills

Cross-disciplinary collaboration

Education

Master's degree in ML/CS/EE

Bachelor's degree with 3+ years industry experience

Tools

AWS

Job description

BigHat Biosciences in San Mateo, CA, seeks a creative ML Scientist or Engineer to advance ML-driven antibody design across discovery to optimization. Our platform uses AI/ML with large proprietary datasets and automated data management to accelerate drug development.

You will apply top-tier ML to refine our protein engineering stack and contribute to turning platforms into real drug candidates. The role involves building state-of-the-art models, multi-objective optimization, LLM-assisted