🛠 Tech Stack

💼 About This Role

You'll lead the delivery of advanced AI model systems powering drug discovery networks for leading pharma and biotech partners. You'll define technical direction, guide architectural decisions, and ensure reliable, high-quality model releases that support real-world drug discovery workflows. This role blends deep hands-on technical execution with strategic leadership, bridging research and production at scale.

🎯 What You'll Do

• Lead end-to-end delivery of federated co-folding and structural biology model systems
• Design, fine-tune, and extend large-scale foundation models for structural biology
• Translate high-level scientific objectives into execution plans and milestones
• Define model evaluation criteria for production-ready drug discovery applications

📋 Requirements

• PhD or MSc in ML, Computational Biology, or related field with 5+ years applied ML experience
• Strong hands-on expertise in structural biology ML (protein modeling, co-folding)
• Proven experience with Python and PyTorch and extending models like OpenFold, AlphaFold, Boltz, or ESM
• Experience with MLOps or ML infrastructure, including Kubernetes-based pipelines

✨ Nice to Have

• Experience in federated learning or privacy-preserving ML
• Experience in regulated environments (pharma, biotech)
• Publication record in top-tier ML or computational biology venues (NeurIPS, ICML, ICLR)

🎁 Benefits & Perks

• 💰 Competitive compensation including early-stage virtual equity
• 🏠 Remote-first work model with flexibility
• 🧘 Wellbeing budget including mental health support, home office allowance, co-working stipend, and learning budget
• 🏖️ Generous annual holiday allowance
• 🤝 Regular onsite gatherings in Berlin or European locations (~3x/year)

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Team Interview· 60 min
4. 4Offer· 30 min