Senior Machine Learning Scientist I/II, Model-Driven Optimization

What you'll do

• Develop optimization methods, property models, and data strategies for protein design and experimental campaigns.
• Build and maintain reliable ML models, software, data workflows, and LLM-enabled or agentic systems.
• Partner with scientists and engineers to integrate platform capabilities, guide technical direction, and deliver experimental impact.

What they ask for

• PhD in machine learning, computational biology, computer science, applied mathematics, engineering, or a related quantitative field.
• Practical experience with probabilistic machine learning, Bayesian optimization, active learning, experimental design, or related sequential decision-making approaches.
• Experience developing ML methods or systems for biological, biomedical, or experimental scientific data.
• Strong Python skills and experience with modern ML frameworks such as PyTorch, JAX, or similar tools.

Nice to have

• Experience in protein design, protein engineering, antibody engineering, biologics discovery, or drug development.
• Experience with multi-objective optimization, uncertainty calibration, model-guided experimental work, deep learning, or LLM agents.

Pay

$192,000 — $265,000 USD base salary per year

Tools

Python, PyTorch, JAX, LLM

AI focus

Builds machine-learning methods and LLM-enabled or agentic workflows to guide therapeutic protein design, experimental selection, and iterative optimization.