ML Scientist I / II, Foundation Models for Life Sciences
Core
Researching and developing large-scale generative models and reasoning frameworks to power automated scientific discovery in life sciences.
Role type
IC foundation model scientist (life sciences)
Builds
Generative models for biological sequences, molecular structures, and multimodal experimental data integrated into a closed-loop discovery engine.
Domain
Life sciences / Generative AI
Deliverable
production ML models
Required skills
Generative model architecture design and training, independent research execution, biological sequence design, molecular structure prediction, ML framework proficiency (PyTorch/JAX/TensorFlow), GPU-based training workflows
Preferred skills
Computational protein design, active learning loops, distributed training infrastructure, high-impact publications in AI for Science
Technologies
PyTorch, JAX, TensorFlow, GPU clusters
Responsibilities
Design, train, and evaluate generative models on biological and chemical data; translate biological questions into ML problems; support data generation strategy and feedback loop design; collaborate with experimental scientists to close the computational-experimental loop
Seniority
Mid-level IC (Scientist I/II)