Principal ML Scientist - Antibody Design

BigHat; California (MO); On-site; USD 254,000 - 290,000; Full time

Benefits offered by this job

Health insurance

Dental & Vision coverage

401(k) with company match

Parental leave

Job summary

BigHat Biosciences seeks a Principal Machine Learning Scientist to advance ML‑driven therapeutic antibody design. You will lead development of generative models and predictive tools on proprietary data and mentor a growing ML team.

You'll drive strategy for future ML research and integrate ML methods with high‑throughput wet labs, enabling fast, scalable antibody discovery and optimization at BigHat.

Qualifications

• PhD in ML/CS or in the hard sciences with 5+ years of post‑graduate experience applying novel ML methods.
• Excellent publications record in major ML venues or journals.
• Strong Python and PyTorch proficiency; software engineering mindset.

Responsibilities

• Design and implement state‑of‑the‑art generative models of antibody sequence and structure, and predictive models of antibody properties.
• Provide leadership and mentorship to ML/data science team members.
• Help set strategy for future ML research aligned with BigHat programs and workflow challenges.
• Develop de novo design methods for initial hits targeting therapeutically relevant proteins.
• Engineer multi‑modality, multi‑objective optimization for lab‑integrated antibody design workflows.

Skills

Python

PyTorch

ML research

Communication

AWS

De novo design

NGS data

Antibody biology

Education

PhD in ML/CS or related hard sciences

Tools

AWS

Job description

BigHat Biosciences seeks a Principal Machine Learning Scientist to advance ML‑driven therapeutic antibody design. You will lead development of generative models and predictive tools on proprietary data and mentor a growing ML team.

You'll drive strategy for future ML research and integrate ML methods with high‑throughput wet labs, enabling fast, scalable antibody discovery and optimization at BigHat.