Executive Director - AI/ML Drug Discovery Analytics

3w3 weeks ago

Revolution Medicines

Redwood City, US · Full-time · $326,000 – $383,000

About this role

Revolution Medicines is a late-stage clinical oncology company developing novel targeted therapies for patients with RAS-addicted cancers. The R&D pipeline includes RAS(ON) inhibitors like daraxonrasib (RMC-6236) and others in clinical development. As Executive Director, AI/ML Drug Discovery Analytics, you will shape data-driven drug discovery.

You will define the Research’s AI/ML strategy and oversee advanced analytics implementation across discovery. Build a world-class team to unlock internal datasets and make insights accessible to scientists. Your work will accelerate early discovery innovation and pipeline progression.

Design robust ML infrastructure with MLOps for seamless model development, deployment, and monitoring. Drive innovation using deep learning, generative models, and diffusion models for target prediction and lead optimization. Leverage unique datasets for novel hypotheses and data-driven decisions.

Define long-term AI/ML vision aligned with priorities and mentor cross-disciplinary teams. Forge partnerships with academic groups and innovators while collaborating across research functions. Act as thought leader, influencing strategic portfolio decisions at scientific forums.

Requirements

Ph.D. or Master's degree in Computer Science, Machine Learning, Physics, Math or a relevant scientific discipline with 10+ years’ experience; exposure to drug discovery a plus
Expertise in a wide variety of AI/ML-based computational techniques and developing adaptable ML workflows to solve challenging problems
Deep understanding of AI/ML techniques such as deep learning, reinforcement learning and generative models
Expertise in frameworks such as PyTorch/TensorFlow, training, and fine-tuning models on GPUs
Track record of deploying AI/ML solutions at scale
Proven track record of leadership and cross-functional collaboration

Responsibilities

Define the Research’s AI/ML strategy and oversee implementation of advanced analytics across discovery
Build, mentor, and inspire a cross-disciplinary team of data scientists, computational chemists, engineers, and biologists
Design and scale a robust ML infrastructure integrating MLOps best practices for model development, deployment, and monitoring
Drive innovation in deep learning, generative models, and diffusion models for target prediction, hit identification, and lead optimization
Leverage RevMed’s unique datasets to generate novel hypotheses and enable data-driven decision-making
Forge partnerships with academic groups, technology innovators, and compute providers
Collaborate across research, chemistry, biology, and IT to integrate AI/ML solutions
Act as a thought leader internally and externally at scientific forums