🛠 Tech Stack

💼 About This Role

You'll lead end-to-end delivery of federated structural biology model systems, turning complex scientific goals into production-ready pipelines. Core impact: driving AI model releases that directly support real-world drug discovery workflows. Join a high-caliber team bridging cutting-edge ML and production at scale.

🎯 What You'll Do

• Lead delivery of federated co-folding and structural biology model systems
• Design, fine-tune, and extend large-scale foundation models (OpenFold, Boltz-2, ESMFold)
• Define technical direction and guide architectural decisions
• Align consortium and internal stakeholders on objectives and evaluation frameworks

📋 Requirements

• PhD or MSc in ML, Computational Biology, or related field with 5+ years applied ML experience
• Hands-on expertise in structural biology ML (protein modeling, co-folding, binding prediction)
• Experience with Python and PyTorch, extending models like OpenFold, AlphaFold, Boltz, or ESM
• Experience with MLOps or ML infrastructure (Kubernetes-based training/evaluation/deployment)

✨ Nice to Have

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

🎁 Benefits & Perks

• 💵 Competitive compensation including early-stage virtual equity
• 🏡 Remote-first working with flexibility to work from anywhere
• 🧠 Wellbeing budget and mental health support
• 🏖️ Generous annual holiday allowance
• 🎯 Cutting-edge AI systems applied to pharmaceutical drug discovery

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Team/Leadership Interview· 60 min