Head of ML Research & Discovery Platforms

Bayer AG; Cambridge (MA); On-site; USD 177,000 - 266,000; Full time

Job summary

Bayer in Cambridge, MA seeks Head of Machine Learning Research to lead ML-driven molecule design across our drug-discovery portfolio. You will define the multi-year technical roadmap, build and lead a team of about 25 scientists and engineers, and ensure ML tools translate into faster, better project decisions.

This hands-on leadership role requires deep fluency in modern ML for molecules, collaboration with medicinal chemistry and structural biology, and a proven ability to deploy models into

Qualifications

• PhD in a molecular science or ML field with depth in both areas.
• Deep, current expertise across ML for molecules: graph neural networks, transformers, generative models.
• Knowledge of SAR interpretation, multi-parameter optimization, ADMET.
• Proven impact on real programs and ability to translate capability into decisions.
• Ability to partner with medicinal chemists and structural biologists.
• Track record delivering software/models into production.

Responsibilities

• Co-own the vision, roadmap, and investment case for ML-driven molecule design and multi-parameter optimization.
• Set standard for model validation, benchmarking, and reporting of failure modes.
• Embed ML into live discovery programs from hit identification through nomination.
• Drive active learning and closed-loop DMTA cycles with integration to automated synthesis.
• Build and lead a team of ~25 scientists and engineers; manage budgets and collaborations.

Skills

Graph neural networks

Transformers

Generative design

Active learning

Uncertainty quantification

Education

PhD in computational chemistry

MSc in related field

Job description

Bayer in Cambridge, MA seeks Head of Machine Learning Research to lead ML-driven molecule design across our drug-discovery portfolio. You will define the multi-year technical roadmap, build and lead a team of about 25 scientists and engineers, and ensure ML tools translate into faster, better project decisions.

This hands-on leadership role requires deep fluency in modern ML for molecules, collaboration with medicinal chemistry and structural biology, and a proven ability to deploy models into