Senior Scientist, ML for Protein Engineering (Remote)

A-Alpha Bio; Seattle (WA); Remote; USD 164,000 - 206,000; Full time

Job summary

A-Alpha Bio is a Seattle-based biotechnology company pioneering AI-driven protein engineering. We seek a Senior Scientist, Machine Learning Research to turn large-scale protein interaction data into actionable insights and models.

The role focuses on developing innovative AI/ML methods for de novo antibody/minibinder design, affinity prediction, and developability optimization. You will collaborate with ML Scientists, interface with wet-lab partners, design experiments, and communicate results

Qualifications

• PhD in a quantitative or life sciences field with 4+ years of software/AI/ML experience; or a 4+ years alternative depending on education
• Strong experience with deep learning frameworks (PyTorch, JAX) and model types (VAEs, Transformers, GNNs)
• Proficiency in data wrangling, model training, cross-validation, and scaling deployments
• Excellent verbal and written communication for cross-disciplinary audiences and external partners

Responsibilities

• Develop AI/ML methods for predicting and engineering protein-protein interactions
• Design rigorous benchmarks and evaluations to ensure reproducibility
• Deliver data packages, model executables, and technical reports on schedule
• Contribute to shared codebase, document methods, and organize data for rollout
• Advance computational approaches to leverage AlphaSeq data for protein engineering
• Lead projects, mentor colleagues, and represent the company at conferences and with collaborators

Skills

Deep learning

PyTorch

JAX

GNNs

Transformers

Protein language models

Data wrangling

Model training

Communication

Education

PhD in quantitative or life sciences

Bachelor's degree in quantitative or life sciences

Tools

AWS

Job description

A-Alpha Bio is a Seattle-based biotechnology company pioneering AI-driven protein engineering. We seek a Senior Scientist, Machine Learning Research to turn large-scale protein interaction data into actionable insights and models.

The role focuses on developing innovative AI/ML methods for de novo antibody/minibinder design, affinity prediction, and developability optimization. You will collaborate with ML Scientists, interface with wet-lab partners, design experiments, and communicate results