🛠 Tech Stack

💼 About This Role

You'll lead end-to-end delivery of federated co-folding models for drug discovery networks, working with foundation models like OpenFold and ESMFold. You'll translate scientific goals into production-ready model pipelines for pharmaceutical partners.

🎯 What You'll Do

• Lead end-to-end delivery of structural biology model systems
• Design, fine-tune, and extend large-scale foundation models
• Define model evaluation criteria for drug discovery
• Own delivery timelines and ensure reliable model releases

📋 Requirements

• PhD or equivalent with 5+ years applied ML in biology
• Strong hands-on expertise in structural biology ML
• Proven experience with PyTorch and large models like OpenFold
• Experience with MLOps and Kubernetes-based pipelines

✨ Nice to Have

• Experience in federated learning
• Publication record in top ML or comp bio venues

🎁 Benefits & Perks

• 💰 Competitive compensation including equity
• 🏠 Remote-first working model
• 🧠 Wellbeing budget and mental health support
• 🌴 Generous holiday allowance
• 🤝 Team gatherings in Berlin three times per year

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter screen· 30 min
2. 2Technical interview· 60 min
3. 3Leadership round· 45 min