Build robust, reproducible and user-friendly pipelines for automated model fine-tuning, alignment and evaluation
Design and implement modular, easy-to-maintain, multi-model pipelines for protein design.
Develop highly scalable ETL pipelines to process petabyte-scale protein data for model pretraining
Optimize model training and inference code to maximize throughput and resource utilization when deployed at scale
Develop software and infrastructure that enable the ML team to work quickly and frictionlessly in distributed and multi-cloud environments
Partner with ML and protein design scientists to prototype research ideas and bring them into production

BS or MS in Computer Science, Machine Learning, or a related field
3+ years of hands-on experience building and training ML models in PyTorch
Strong Python and software engineering fundamentals, including testing, code quality, and version control
Experience profiling, benchmarking, and optimizing ML model training and inference
Experience implementing or optimizing transformer-based architectures
Familiarity with cloud infrastructure and containerization (GCP, AWS, Azure, Kubernetes, Docker)
Strong fundamentals in ML, statistics, and/or linear algebra

Competitive compensation package with equity participation
401(k) with a strong employer match
Comprehensive benefits including health/dental/vision insurance
Generous PTO policy and commitment to work-life balance
Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Machine Learning Engineer

Key skills