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About the Role

We are seeking a scientific and technical leader to make AI & machine learning central to how we design and optimize molecules across our discovery portfolio. You will sit on the Data Science & AI leadership team and be accountable for the models, platforms, and ways of working that shorten design-make-test-analyze cycles and raise our probability of delivering high-quality candidates. This is a hands-on strategy role, not research-only or delivery-only. You will set a multi-year technical roadmap, build and lead a team of 25, and be measured by whether project teams make better decisions and reach candidate faster because of the capabilities you build. It demands fluency in both modern AI/ML and the medicinal chemistry and structural biology realities of drug discovery — expect to spend as much time in project reviews as in model architecture discussions.

Responsibilities

Define and deliver an AI/ML molecular design strategy aligned with current and future Drug Discovery priorities.
Make rigorous build/buy/partner decisions for generative design, property prediction, structure-based ML, synthesis planning, foundation models, and external platforms.
Establish robust model-validation standards, including prospective benchmarking, uncertainty quantification, applicability domains, reproducibility, and transparent reporting of limitations.
Monitor the external AI/ML landscape, identify disruptive developments early, and secure access to best-in-class capabilities.
Embed ML into live discovery programs by partnering closely with medicinal chemistry, computational design, structural biology, biophysics, screening, DMPK, safety, and Drug Discovery Sciences.
Co-own program outcomes from hit identification through candidate nomination, optimizing potency, selectivity, ADMET, developability, synthetic feasibility, and IP position.
Lead development of core platforms for ADMET/property prediction, generative and de novo design, retrosynthesis, synthetic accessibility, co-folding, pose prediction, docking rescoring, and ML-accelerated free-energy methods.
Build a scalable data and MLOps foundation with curated and harmonized assay, structural, and DMTA data; ensuring provenance, feedback capture, versioning, monitoring, documentation, and reproducibility.
Lead and develop a high-performing interdisciplinary organization; managing strategic investments and external partnerships while fostering scientific excellence, collaboration, and measurable portfolio value.

Requirements

Hold a PhD in computational chemistry, cheminformatics, structural biology, biophysics, computer science, or a related field, with demonstrated depth in both molecular science and machine learning. Exceptional MSc candidates with equivalent experience will be considered.
Bring extensive relevant experience, including strong exposure to leading technical teams; experience leading leaders is strongly preferred.
Have experience in a large matrixed pharma R&D organization, or scaling a capability from startup to enterprise.
Possess deep, current expertise in ML for molecules: graph neural networks, transformers, generative methods (diffusion, flow matching, autoregressive), Bayesian optimization and active learning, transfer learning on sparse assay data, and uncertainty quantification.
Have a working command of the discovery domain: SAR interpretation, multi-parameter optimization, ADMET and developability, protein structure and ligand binding, docking and free energy methods.
Demonstrate impact on real programs, with advanced molecules, cycles shortened, and decisions changed; a publication record alone is not sufficient.
Have the credibility to partner with medicinal chemists and structural biologists as a scientific peer, and to challenge and be challenged on design decisions.
Have a track record of delivering models and software into production use by scientists, not just prototypes.
Bring experience beyond conventional small molecules: PROTACs and molecular glues, macrocycles, peptides, covalent inhibitors, or oligonucleotides.
Maintain a strong external profile: publications, conference presence, or leadership in precompetitive consortia.
Speak English fluently.

Skills

AI/ML
Machine Learning
Molecular Design
Generative Design
Property Prediction
Structure-based ML
Synthesis Planning
Foundation Models
Model Validation
Prospective Benchmarking
Uncertainty Quantification
Applicability Domains
Reproducibility
Transparent Reporting
Graph Neural Networks
Transformers
Diffusion Models
Flow Matching
Autoregressive Models
Bayesian Optimization
Active Learning
Transfer Learning
SAR Interpretation
Multi-parameter Optimization
ADMET
Developability
Protein Structure
Ligand Binding
Docking
Free Energy Methods
PROTACs
Molecular Glues
Macrocycles
Peptides
Covalent Inhibitors
Oligonucleotides
MLOps
Data Curation
Data Harmonization
Assay Data
Structural Data
DMTA Data
Data Provenance
Feedback Capture
Data Versioning
Data Monitoring
Data Documentation

Location

Germany: Berlin: Berlin

Work Type

Full-time

Experience Level

Senior Leadership
Team Lead
Experience leading leaders strongly preferred

Education Level

PhD in computational chemistry, cheminformatics, structural biology, biophysics, computer science, or a related field
Exceptional MSc candidates with equivalent experience will be considered

Salary/Compensations

129.700€ - 163.800€ per year

Benefits

Competitive salary plus a variable component and a global equity-based cash plan.
Loving company daycare centers at multiple locations.
Support in finding childcare.
Time off for the care of elderly or dependent family members.
Summer camps for children.
Access to learning and development opportunities.
Training programs through the Bayer Learning Academy.
Development dialogues.
Coaching and mentoring programs.
Free health checks with the company doctor.
Inclusive work environment.

About the Company

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’.
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.
This is your opportunity to tackle the world’s biggest challenges with us: Maintaining our health, feeding growing populations and slowing the rate of climate change.
You have a voice, ideas and perspectives and we want to hear them. Because our success begins with you. Be part of something big. Be Bayer.

Equal Opportunity

Bayer welcomes applications from all individuals, regardless of race, national origin, gender, age, physical characteristics, social origin, disability, union membership, religion, family status, pregnancy, sexual orientation, gender identity, gender expression or any unlawful criterion under applicable law. We are committed to treating all applicants fairly and avoiding discrimination.