Director Machine Learning, Drug Discovery Analytics

Revolution Medicines; San Francisco (CA); On-site; USD 273,000 - 321,000; Full time

Job summary

Revolution Medicines is seeking a Director of Machine Learning to lead the development of advanced machine learning approaches that accelerate small-molecule drug discovery. This role sits at the intersection of data science, chemistry, and biology, transforming complex scientific datasets into predictive models that guide target discovery, compound design, and translational hypotheses.

Working closely with experimental scientists, the Director ML will develop cutting-edge modeling approaches

Qualifications

• PhD in machine learning, computational chemistry, computational biology, computer science, or a related quantitative discipline.
• 8+ years applying machine learning or advanced analytics to scientific problems.
• Demonstrated experience working with chemical or biological datasets in drug discovery or related domains.
• Strong expertise in Python-based ML ecosystems (PyTorch, TensorFlow, scikit-learn), data analysis (NumPy, Pandas), and deep learning techniques.

Responsibilities

• Provide hands-on scientific leadership in drug discovery analytics spanning AI and analytics for scientific decision-making.
• Managing, coaching and mentoring scientists to develop skills and organizational capability.
• Define and lead ML strategies that accelerate early-stage drug discovery.
• Develop predictive models for activity, selectivity, ADME/Tox and developability properties; target engagement and phenotypic data.
• Collaborate with biologists and data scientists to deploy models in scalable discovery workflows.

Skills

Python-based ML ecosystems

Deep learning & representationLearning

Mentorship & coaching

Drug discovery domain familiarity

Education

PhD in machine learning or related quantitative discipline

Tools

PyTorch

TensorFlow

scikit-learn

NumPy

Pandas

Job description

Revolution Medicines is a late-stage clinical oncology company developing novel targeted therapies for patients with RAS-addicted cancers. The company’s R&D pipeline comprises RAS(ON) inhibitors designed to suppress diverse oncogenic variants of RAS proteins. The company’s RAS(ON) inhibitors daraxonrasib (RMC-6236), a RAS(ON) multi-selective inhibitor; elironrasib (RMC-6291), a RAS(ON) G12C-selective inhibitor; zoldonrasib (RMC-9805), a RAS(ON) G12D-selective inhibitor; and RMC-5127, a RAS(ON) G12V-selective inhibitor, are currently in clinical development. As a new member of the Revolution Medicines team, you will join other outstanding professionals in a tireless commitment to patients with cancers harboring mutations in the RAS signaling pathway.

The Opportunity:

We are seeking a Director Machine Learning to lead the development of advanced machine learning approaches that accelerate small-molecule drug discovery. This role sits at the intersection of data science, chemistry, and biology, transforming complex scientific datasets into predictive models that guide target discovery, compound design, and translational hypotheses.

Working closely with experimental scientists, the Director ML will develop cutting-edge modeling approaches that integrate chemical, biological, and phenotypic data with their team. The successful candidate will play a key role in advancing a data-driven discovery strategy by designing predictive models, deploying innovative algorithms, and translating insights into actionable decisions that improve the speed and success of the discovery of medicines for patients with RAS-driven cancers.

Key responsibilities include:

Scientific Leadership:

• Provide hands-on scientific leadership in drug discovery analytics spanning Identify opportunities where AI and advanced analytics can meaningfully improve scientific decision-making
• Managing, coaching and mentoring scientists across the function in order to develop their skills and build RevMed’s organizational capabilities
• Define and lead machine learning strategies that accelerate early-stage drug discovery.

Model Development:

• Develop predictive models for:
  • Compound activity, selectivity, ADME/Tox, and developability properties
  • Target engagement, mechanism-of-action, and phenotypic datasets

Cross-Functional Collaboration:

• Work with biologists to interpret complex experimental datasets and generate mechanistic hypotheses.
• Collaborate with data scientists and engineers and ML engineers to deploy models into scalable discovery workflows.

Required Skills, Experience and Education:

• PhD in machine learning, computational chemistry, computational biology, computer science, or a related quantitative discipline.
• 8+ years experience applying machine learning or advanced analytics to scientific problems.
• Demonstrated experience working with chemical or biological datasets in drug discovery or related domains.
• Strong expertise in:
  • Python-based ML ecosystems (PyTorch, TensorFlow, scikit-learn)
  • Data analysis and scientific computing (NumPy, Pandas)
  • Deep learning and representation learning techniques
• Evidence of successful coaching, mentorship and development of both individuals and teams in order to build long-term organizational capability
• Passion for scientific innovation and a relentless commitment to improving patient outcomes.

Preferred Skills:

• Proven track record of applying advanced AI/ML approaches (deep learning, generative modeling, structure-based ML) to drug discovery or related life sciences domains.
• Experience with cheminformatics or bioinformatics toolkits is highly desirable.
• Familiarity with cloud computing and scalable ML workflows is a plus
• Ability to work at the interface of computational and experimental science.

The base pay salary range for this full-time position for candidates working onsite at our headquarters in Redwood City, CA is listed below.

Base Pay Salary Range

$273,000 - $321,000 USD

Please note that base pay salary range is one part of the overall total rewards program at RevMed, which includes competitive cash compensation, robust equity awards, strong benefits, and significant learning and development opportunities.

Revolution Medicines is an equal opportunity employer and prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity/expression, national origin/ancestry, age, disability, marital status, medical condition, and veteran status.

Revolution Medicines takes protection and security of personal data very seriously and respects your right to privacy while using our website and when contacting us by email or phone. We will only collect, process and use any personal data that you provide to us in accordance with our CCPA Notice and Privacy Policy. For additional information, please contact [e-mail].