Senior Machine Learning Scientist I, Model-Driven Optimization

📋 Description

• Develop ML methods and systems for lab-in-the-loop protein optimization.
• Shape data-generation strategies for informative campaigns and model improvement.
• Build LLM-enabled workflows to explore design hypotheses and connect models to data.
• Design, test, and maintain production-grade ML models, components, and data workflows.
• Partner with ML engineering and software teams to integrate components into platform capabilities.
• Collaborate with protein designers and wet-lab scientists to ground models in experiments.

🎯 Requirements

• PhD in ML, computational biology, CS, applied mathematics, engineering, or related quantitative field.
• Strong practical experience with probabilistic ML, Bayesian optimization, active learning, or sequential decision-making.
• Experience developing ML methods or systems for biological/experimental data with noisy assays and sparse labels.
• Demonstrated ability to translate ML ideas into systems, tools, or workflows that affect decisions.
• Strong Python skills and experience with PyTorch, JAX, or similar tools.
• Strong systems thinking; design interfaces; partner with engineering teams to build scalable ML infrastructure.

🎁 Benefits

• Annual bonus and equity compensation.
• Competitive benefits package.
• Opportunity to shape ML for protein design with real-world impact.