We are currently looking for a Technical Lead - Structural Biology Networks in Spain.
This is a high-impact technical leadership role at the intersection of structural biology, foundation models, and federated machine learning. You will lead the delivery of advanced AI model systems powering drug discovery networks used by leading pharmaceutical and biotech partners. You will define technical direction, guide architectural decisions, and ensure reliable, high-quality model releases that directly support real-world drug discovery workflows. Lead the end-to-end delivery of federated co-folding and structural biology model systems, staying deeply involved in modeling, architecture, evaluation, and engineering execution.
Design, fine-tune, and extend large-scale foundation models for structural biology, including systems such as OpenFold, Boltz-2, and ESMFold, ensuring robust and production-ready outputs.
Define and enforce model evaluation criteria, ensuring high-quality, validated results suitable for real-world drug discovery applications.
Align consortium and internal stakeholders on objectives, data requirements, evaluation frameworks, and delivery expectations.
PhD, MSc, or equivalent experience in Machine Learning, Computational Biology, Computer Science, or a related field, with 5+ years of applied ML experience in complex scientific or biological domains.
Strong hands-on expertise in structural biology ML, including protein modeling, co-folding, or binding prediction.
Proven experience working with modern ML frameworks such as Python and PyTorch, and extending large-scale models like OpenFold, AlphaFold, Boltz, or ESM.
Experience with MLOps or ML infrastructure, including Kubernetes-based training, evaluation, or deployment pipelines.
Demonstrated ability to lead complex ML delivery projects, define technical direction, and drive teams toward production-quality releases.
Bonus: experience in federated learning, distributed training, or privacy-preserving ML environments.
Bonus: experience in regulated or high-trust environments (pharma, biotech, enterprise ML systems).
Bonus: publication record in top-tier ML or computational biology venues (NeurIPS, ICML, ICLR, ISMB, RECOMB, etc.).
Competitive industry compensation, including early-stage virtual equity options.
Remote-first working model with flexibility to work from anywhere.
Wellbeing budget, mental health support, home office allowance, co-working stipend, and learning budget.
Generous annual holiday allowance.
High-caliber, execution-focused team with experience from leading global organizations.
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