Senior / Principal ML Scientist, Foundation Models for Life Sciences

Highlights

• Build large-scale training pipelines for structure prediction and co-folding models.
• Scale inference to campaign scale to accelerate automated antibody design workflows.
• Drive Lab-in-the-Loop discovery by integrating models with experimental feedback.

What they offer

• Competitive base compensation with bonus potential and early-stage equity
• Medical, dental and vision coverage
• Employer-paid life and disability insurance
• Flexible time off with company-wide holidays and paid parental leave
• Educational assistance, commuter benefits and subsidized lunch

Ideal candidate

ML systems builder who thrives at the research-to-production interface and wants to power automated scientific discovery. You care about reliability at scale and closing the loop between computation and experiment in life sciences.

Requirements

• Master's degree or higher in Computer Science, Machine Learning or related quantitative field
• Extensive hands-on experience building and operating production ML systems at scale
• Deep expertise in distributed training infrastructure including large-scale GPU clusters
• Strong software engineering fundamentals: system design, CI/CD, observability and reliability
• Proficiency in ML frameworks with training and inference performance optimization
• Demonstrated ability to drive technical direction for ML infrastructure independently
• Track record of cross-functional collaboration with research scientists