Director/Senior Director, AI/ML for Drug Discovery

The role

This leader will lead the Data Science function by implementing advanced machine learning and statistical approaches. The role uses proprietary GPCR structural and assay data to advance small-molecule drug discovery programs.

What you will do

• Lead Septerna’s Data Science team, providing technical direction and developing team capabilities.
• Develop and execute a roadmap for implementing state-of-the-art AI/ML approaches using GPCR structural data.
• Identify and integrate emerging technologies into Septerna’s computational stack.
• Oversee and extend analysis pipelines including DNA-encoded library, high-throughput screening, and assay-data workflows.
• Advance and support ML-QSAR models to impact DMTA cycles and generative chemistry workflows.
• Refine data-engineering and cloud-infrastructure requirements and establish best practices for data curation and model validation.

Required qualifications

• PhD in computational biology, computational chemistry, or a degree in computer science, applied mathematics or statistics focused on modeling biological systems.
• Minimum of 10+ years of relevant industry experience including application of machine learning to diverse scientific problems.
• Demonstrated leadership in machine learning for drug discovery.
• Track record of building and applying predictive models to real-world, noisy, and multimodal scientific datasets.
• Experience applying co-folding or hybrid models to enable productive ligand pose prediction on membrane proteins and flexible protein classes.
• Previous work transfer learning or fine-tuning foundation models and using appropriate metrics.
• Experience leading teams and serving as the senior technical lead of cross functional initiatives.
• Expertise in PyTorch, scikit-learn, numpy, pandas, pyarrow, and RDKit.
• Deep knowledge of gradient boosting decision trees (XGBoost, LGBM), graph neural networks (GNN/D-MPNN), transformers, generative modeling, active learning, and Bayesian optimization.
• Extensive experience with cloud and distributed computing environments, including AWS, GCP, or Azure.
• Experience building and maintaining containerized machine-learning workflows.
• Track record in MLOps and partnering with software and platform engineering teams.

Nice to have

• Experience with molecular property prediction, generative chemistry, graph neural networks, protein–ligand modeling, sequence modeling, or physics-informed machine learning.
• Hands on structure-based drug discovery and experience collaborating closely with Computational Chemistry teams.
• Publications, patents, or open-source contributions in relevant scientific or machine-learning domains.

Benefits

• stock options
• annual target bonus

About the company

Septerna is a biotechnology company based in South San Francisco, CA. The company uses a Native Complex Platform™ to develop life-changing medicines by targeting G protein-coupled receptors (GPCRs).