Lead teams building and delivering federated large molecule AI systems, staying hands-on across antibody modeling, co-folding, binder prediction, and developability
Build and implement ML applications large biomolecular foundation models such as OpenFold, Boltz-2 and ESM
Own delivery of these against committed milestones and ensure high-quality model releases ship on time
Translate ambiguous scientific and technical goals into clear plans, priorities, workstreams, and decisions
Guide evaluation decisions and build on them to deliver results packages to external stakeholders
Surface risks, blockers, bugs, timeline changes, and technical trade-offs early, with clear recommendations
Align consortium members on objectives, evaluation criteria, data requirements, timelines, and delivery expectations
Work with product, engineering, research, and leadership to ensure application requirements shape the model roadmap.

PhD, MSc, or equivalent experience in a relevant field
5+ years applying ML to complex scientific or biological problems, ideally in structural biology, antibody engineering, biologics discovery, developability prediction, binder prediction or protein design
Hands-on experience with modern ML systems in Python and PyTorch
Worked with or extended large-scale models such as OpenFold, AlphaFold, Boltz, ESM, or similar
MLOps or ML infrastructure experience, particularly with Kubernetes-based training, evaluation, or deployment workflows
Define success criteria, validate model quality, and ensure ML releases are robust enough for real-world use
Led delivery of complex ML projects, including setting technical direction, managing risks and dependencies, and driving teams toward high-quality releases
Comfortable operating as a player-coach: mentoring engineers and ML scientists while contributing directly to modeling, experimentation, or architecture when needed
Work effectively with product, research, leadership, customers, and scientific stakeholders to turn ambiguous requirements into clear technical plans.

Industry-competitive compensation, including early-stage virtual share options
Remote-first working – work where you work best
Wellbeing budget, mental health support, work-from-home budget, co-working stipend, and learning budget
Generous holiday allowance
Office Days at our Berlin HQ or a different European location (3x per year)
A high-calibre, execution-focused team with experience from leading organizations

Technical Lead – Large Molecule AI Systems

Key skills