Senior Machine Learning Scientist I, Model-Driven Optimization
Core
Building ML methods, data strategies, and closed-loop systems for lab-in-the-loop protein optimization to discover and optimize therapeutic proteins.
Role type
Senior IC machine learning scientist (model-driven optimization)
Builds
Production ML models, data workflows, and agentic systems for protein design
Domain
Biomedical / Protein engineering / Generative biology
Deliverable
production ML models
Required skills
Probabilistic machine learning, Bayesian optimization, active learning, experimental design, Python, PyTorch/JAX, systems thinking, multi-objective optimization
Preferred skills
Protein design, antibody engineering, deep learning (transformers), LLM agents, high-throughput screening
Technologies
PyTorch, JAX, LLMs
Responsibilities
Develop ML methods for lab-in-the-loop protein optimization; Shape data-generation strategies for experimental campaigns; Build and apply LLM-enabled agentic workflows; Design and maintain production-quality ML models and data workflows; Partner with engineering to integrate scalable platform capabilities; Collaborate with wet-lab scientists to ground models in experimental reality; Define technical direction and milestones for cross-functional programs.
Seniority
Senior, hands-on IC