Head of Machine Learning Research

Bayer CropScience Limited; New Hanover Township (NJ); On-site; USD 177,000 - 266,000; Full time

Job summary

Bayer is seeking a Head of Machine Learning Research to advance ML-enabled design across our drug discovery portfolio. You will co-own the vision, roadmap, and investments for generative design, structure-based ML, and DMTA cycles, aligning chemistry and biology to accelerate nomination.

As a scientific leader, you will deliver reliable ML products to scientists, drive governance for model validation, and manage external collaborations while growing a team of ~25 across ML research,

Qualifications

• PhD/MSc with demonstrated depth in molecular science and ML.
• Expertise in modern ML for molecules and uncertainty quantification.
• Experience translating ML research into real programs with impact.

Responsibilities

• Define strategy and technical direction for ML-driven molecule design and optimization.
• Lead delivery of models and platforms to accelerate discovery across programs.
• Build and manage a team of ML researchers, computational chemists, and ML engineers (≈25).
• Collaborate with medicinal chemistry and structural biology to embed ML into live projects.

Skills

ML for molecules

GNNs & transformers

SAR interpretation

ADMET & developability

Production-ready ML software

Uncertainty quantification

Leadership in ML research

Education

PhD in computational chemistry / cheminformatics / structural biology

MSc with equivalent depth

Job description

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none' is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining 'impossible'. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

Head of Machine Learning Research

We are seeking a scientific and technical leader to advance machine learning–enabled molecular design across our drug discovery portfolio. As a member of the Data Science & AI leadership team, you will define and deliver the models, platforms, and ways of working that shorten design–make–test–analyze cycles and improve the quality of molecules progressing toward nomination.

YOUR TASKS AND RESPONSIBILITIES

Strategy and Technical Direction

• Co-own the vision, roadmap, and investment case for ML-driven molecule design and multi-parameter optimization across small molecules and emerging modalities.
• Make build/buy/partner decisions across generative design, property prediction, structure-based ML, and synthesis planning; evaluate foundation models and external platforms with rigor rather than hype.
• Set the standard for how models are validated, benchmarked prospectively, and retired — including uncertainty quantification, applicability domain, and honest reporting of failure modes.

Delivery into Discovery Projects

• Partner with Drug Discovery Sciences — medicinal chemistry, structural biology, biophysics, screening, DMPK, and safety — to embed ML into live programs from hit identification through candidate nomination.
• Co-own program-level design goals with chemistry leads: potency, selectivity, ADMET, developability, and IP position optimized together rather than sequentially.
• Drive active learning and closed-loop DMTA cycles, including integration with high-throughput and automated synthesis where available.
• Ensure models are delivered as reliable, supported products that chemists actually use, not one-off analyses.

Platform and Data Foundation

• Direct development of core capabilities: ADMET and property predictors, generative and de novo design, retrosynthesis and synthetic accessibility, and structure-based ML including co-folding, pose prediction, docking rescoring, and ML-accelerated free energy methods.
• Work with data engineering to secure the assay, structural, and DMTA data foundation these models depend on — curation, provenance, harmonization across assays and sites, and feedback capture from every make-test cycle.
• Establish MLOps practice appropriate to a regulated R&D environment: versioning, reproducibility, monitoring, and documentation.

Leadership and Organization

• Build, lead, and develop a team of approximately 25 spanning ML research, computational chemistry, and ML engineering; grow leaders within the group.
• Own budget, vendor relationships, and external collaborations with academic groups, consortia, and biotech partners.
• Represent the function to R&D leadership, translating technical capability into portfolio impact and translating portfolio priorities into technical strategy.
• Contribute to the broader scientific community through publication, presentation, and precompetitive collaboration where appropriate.

WHO YOU ARE

Required Qualifications

• PhD in computational chemistry, cheminformatics, structural biology, biophysics, computer science, or a related field, with demonstrated depth in both a molecular science and machine learning. Exceptional candidates with an MSc and equivalent depth of experience will be considered;
• Deep, current expertise across modern ML for molecules: graph neural networks, transformers, generative approaches (diffusion, flow matching, autoregressive), Bayesian optimization and active learning, transfer learning on sparse assay data, and uncertainty quantification;
• Working command of the discovery domain: SAR interpretation, multi-parameter optimization, ADMET and developability, protein structure and ligand binding, docking and free energy methods;
• Demonstrated impact on real programs — molecules advanced, cycles shortened, decisions changed. A publication record without program impact is not sufficient for this role;
• Proven ability to partner with medicinal chemists and structural biologists as scientific peers, including the credibility to challenge and be challenged on design decisions;
• Track record of delivering software or models into production use by scientists, not just prototypes.

Preferred Qualifications

• 12+ years of relevant experience, including 5+ years leading technical teams; experience leading leaders strongly preferred.
• Experience with modalities beyond conventional small molecules — PROTACs and molecular glues, macrocycles, peptides, covalent inhibitors, or oligonucleotides;
• Familiarity with lab automation, self-driving lab concepts, or high-throughput chemistry integration;
• Experience evaluating or deploying large-scale pretrained models for chemistry or protein structure;
• Prior experience in a large matrixed pharma R&D organization, or scaling a capability from startup to enterprise;
• Strong external profile: publications, conference presence, or leadership in precompetitive consortia.

Employees can expect to be paid a salary between $177,400.00 - $266,200.00. Additional compensation may include a bonus or commission (if relevant). Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc.

This salary range is merely an estimate and may vary based on an applicant’s location, market data/ranges, an applicant’s skills and prior relevant experience, certain degrees and certifications, and other relevant factors.

This posting will be available for application until at least 09/29/2026.

Bayer is an Equal Opportunity Employer/Disabled/Veterans

Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.

Bayer is a E-Verify Employer.

Location:| United States : Massachusetts : Cambridge || United States : New Jersey : Whippany |

Division:| Pharmaceuticals

Email:| [e-mail]