🛠 Tech Stack

💼 About This Role

You'll lead a new ML Research team at the intersection of AI and structural biology for drug discovery. You'll drive the design and deployment of large-scale models like co-folding models while remaining hands-on in experimentation. This player-coach role combines research excellence with applied impact in pharmaceutical R&D.

🎯 What You'll Do

• Establish and lead the ML Research team, defining scientific vision and direction.
• Design and train large-scale foundation models for structural biology.
• Refine data pipelines and model architectures using proprietary datasets.
• Translate research into production-ready modeling for drug discovery.

📋 Requirements

• PhD or MSc in CS, ML, or Computational Biology with 7+ years experience.
• Strong expertise in structural biology (co-folding, protein modeling).
• Proven publication record in top-tier ML or comp bio venues.
• Hands-on experience with PyTorch and large-scale models (e.g., OpenFold).

✨ Nice to Have

• Experience building ML research functions from scratch in early-stage biotech.
• Familiarity with distributed training on GPU/cloud platforms (AWS, Azure).
• Exposure to federated learning or privacy-preserving ML.

🎁 Benefits & Perks

• 💻 Remote-first working model with flexibility from anywhere.
• 💰 Competitive compensation including virtual share options.
• 🏠 Home office allowance and co-working stipend.
• 📚 Learning budget and wellbeing support.
• ✈️ In-person company gatherings (3x/year in Europe).

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter call· 30 min
2. 2Technical interview· 60 min
3. 3On-site presentation· 90 min