Senior Data Scientist - Protein Structure ML models

Overview

Senior Data Scientist role focused on building and validating protein structure machine learning models for AI-enabled protein and antibody design in Large Molecule Discovery.

What you'll do

• Build and adapt machine learning models that predict protein function from structure, with emphasis on antibodies and antibody-like molecules.
• Design and maintain validation tasks and curated benchmarks for assessing antibody binding models across internal and external datasets.
• Partner with wet-lab scientists to guide assays for collecting property data used for model training and validation.
• Develop integrated protein design workflows chaining structure prediction, structure generation, and inverse-folding models.
• Translate validation results into guidance for model selection, model improvement, and downstream protein design decisions.

What you'll need

• Bachelor’s degree in a relevant quantitative field (e.g., computational biology/bioinformatics/life sciences/data science) and 6+ years of relevant experience OR Master’s plus 4+ years OR PhD plus unspecified experience.
• Fluency in Python and ability to develop reliable, reusable scientific software.
• Hands-on experience with at least one modern deep learning framework (e.g., PyTorch or JAX).
• Strong foundation in protein structure modeling, particularly for antibodies and antibody-like molecules.
• Experience applying deep learning to protein structures, including graph neural networks and/or equivariance-aware methods.
• Experience using generative protein structure tools (e.g., RFdiffusion or Boltzgen) for protein design questions.

Details

• Location: Hyderabad, India.