Senior Scientist I, Computational Protein Design

What you'll do

• Lead research from scientific hypotheses through computational implementation and experimental proof of concept, producing validated, reusable capabilities.
• Develop protein-design methods, scoring tools, benchmarks, and reproducible evaluation workflows; assess performance, uncertainty, and failure modes.
• Build agentic design workflows and collaborate with experimental, application, machine-learning, and engineering teams to test and scale successful approaches.

What they ask for

• Strong quantitative foundations and practical fluency in machine learning and computational methods relevant to protein science, molecular modeling, or biological design.
• Record of translating research into reusable computational methods, models, software, or workflows and demonstrating value on biological problems.
• Experience with rigorous benchmarks or evaluation frameworks and applied biological or therapeutic problems involving cross-functional teams.
• Hands-on computational skills, including Python and PyTorch or JAX, plus strong understanding of protein structure, sequence–structure–function relationships, molecular interactions, and biophysics.

Nice to have

• Experience building LLM-enabled agents, scientific copilots, or multi-agent systems for therapeutic design or scientific hypothesis generation and testing.
• PhD in a relevant scientific or engineering discipline, with at least three years of industry experience following completion of the PhD and ability to lead consequential technical work independently.

Pay

$172,000 — $241,000 USD base salary per year

Tools

Python, PyTorch, JAX

AI focus

Develops computational protein-design methods using generative, predictive, and biophysical approaches, and builds agentic and multi-agent workflows that connect scientific information, models, internal data, analysis tools, and experimental results. Establishes human oversight, traceability, and reliability measures.