🛠 Tech Stack

💼 About This Role

You'll lead delivery of AI model systems for drug discovery networks used by top pharma and biotech partners. This role combines deep hands-on technical execution with strategic leadership, turning complex scientific goals into production-ready pipelines.

🎯 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 like OpenFold, Boltz-2, and ESMFold.
• Translate scientific objectives into clear execution plans and delivery milestones.
• Define and enforce model evaluation criteria for real-world drug discovery.

📋 Requirements

• PhD, MSc, or equivalent with 5+ years of applied ML in scientific or biological domains.
• Strong hands-on expertise in structural biology ML including protein modeling or co-folding.
• Experience with Python and PyTorch and extending models like OpenFold, AlphaFold, 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 like pharma or biotech.
• Publication record in top-tier ML or computational biology venues.

🎁 Benefits & Perks

• 💰 Competitive compensation with early-stage virtual equity.
• 🏠 Remote-first working model.
• 🏖️ Generous annual holiday allowance.
• 🧠 Wellbeing budget including mental health support and learning budget.
• 🤝 Regular onsite team gatherings in Berlin or Europe (~3 times/year).

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Final Interview· 60 min