Senior Scientist, Machine Learning; Biologics Design

Senior Scientist (Machine Learning for Large Molecule Design)
Key Responsibilities

• Develop and apply ML models for biologics design, including sequence-to-function, structure‑aware, and multi‑objective models that support lead optimization decisions
• Implement data‑efficient modeling strategies (e.g., active learning, Bayesian optimization, experimental design) to prioritize designs and guide iterative experimentation
• Apply and extend modern deep learning approaches relevant to biologics, including protein language models, geometric deep learning, and generative methods (e.g., diffusion, inverse folding, Protein
  
  MPNN‑style approaches)
• Perform structure‑based modeling and analysis of antibodies and multispecifics
• Partner closely with protein therapeutics, structural biology, assay, and engineering teams to translate computational results into experimental decisions

• PhD in Computational Biology, Computer Science, Mathematics, Physics, Chemistry, Bioengineering, or a related quantitative discipline, and 2+ years of experience
• Strong proficiency in Python and deep learning frameworks such as PyTorch (and/or JAX), plus standard scientific libraries (Num Py, pandas, etc.)
• Demonstrated experience architecting, training, and evaluating deep learning models (representation learning, multimodal learning, geometric deep learning, or generative modeling)
• Solid understanding of protein structure, antibody architecture, and biophysical principles relevant to large‑molecule therapeutics
• Demonstrated research productivity (e.g., first‑author publications) and ability to communicate clearly to diverse audiences

• Experience with molecular modeling or simulations (Amber, OpenMM, Rosetta, CHARMM, coarse‑grained or multi‑scale methods)
• Experience developing production‑grade ML tooling (experiment tracking, model registries, CI/testing, containerization, workflow orchestration)
• Prior industry experience in biologics discovery, protein engineering, or therapeutic protein development

• Salary range: $ - $
• May be eligible for a discretionary annual bonus, discretionary stock‑based long‑term incentives, paid time off, and benefits including company‑sponsored medical, dental, vision, and life insurance

For current employees and contractors: apply via the Internal Career Opportunities portal in Workday.