Head of Machine Learning Research

At Bayer were visionaries driven to solve the worlds toughest challenges and striving for a world where Health for all Hunger for none is no longer a dream but a real possibility. Were 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 youre hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference theres only one choice.

Head of Machine Learning Research

We are seeking a scientific and technical leader to advance machine learningenabled 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 designmaketestanalyze cycles and improve the quality of molecules progressing toward nomination.

This is a hands-on strategic leadership roleneither research-only nor delivery-only. You will set a multi-year technical roadmap build and lead a team of approximately 25 scientists and engineers and ensure that machine learning capabilities translate into better project decisions and faster progression to candidate selection.

You will lead the development and application of modern machine learning methodsincluding deep learning neural networks ensemble methods natural language processing and machine perceptionto complex high-dimensional scientific data. Your team will develop predictive and generative models that help discovery scientists understand biological and chemical patterns prioritize experiments optimize molecular properties and design novel molecules.

Success in this role requires deep fluency in contemporary machine learning combined with a practical understanding of the realities of medicinal chemistry structural biology and drug discovery. You will spend as much time engaging in project-team reviews and scientific decision-making as you do shaping model architectures platform strategy and technical standards

YOUR TASKS AND RESPONSIBILITIES

The primary responsibilities of this role Head of Machine Learning Research are to:

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

Bayer seeks an incumbent who possesses the following:

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 $177400.00 - $266200.00. 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 applicants location market data/ranges an applicants 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.