[Remote] Technical Lead - Structural Biology Networks

Note: The job is a remote job and is open to candidates in USA. Apheris is pioneering the application of AI in pharmaceutical R&D, focusing on enhancing drug discovery processes. The Technical Lead will oversee AI Structural Biology model programs, ensuring the delivery of high-quality models while mentoring teams and managing technical challenges.ResponsibilitiesLead the teams building and delivering federated co-folding models, staying hands-on across modeling, architecture, evaluation, and engineering executionBuild and implement ML applications in structural biology, particularly around fine-tuning and extending foundational models like OpenFold, Boltz-2 and ESMFold. Own delivery of these against committed milestones and ensure high-quality model releases ship on timeTranslate ambiguous scientific and technical goals into clear plans, priorities, workstreams, and decisions. Guide evaluation decisions and build on them to deliver results packages to external stakeholdersSurface risks, blockers, bugs, timeline changes, and technical trade-offs early, with clear recommendationsAlign consortium members on objectives, evaluation criteria, data requirements, timelines, and delivery expectationsWork with product, engineering, research, and leadership to ensure application requirements shape the model roadmapSkillsYou have a PhD, MSc, or equivalent experience in a relevant field, plus 5+ years applying ML to complex scientific or biological problems, ideally in structural biology, protein modeling, co-folding, or binding predictionYou have hands-on experience with modern ML systems in Python and PyTorch, and have worked with or extended large-scale models such as OpenFold, AlphaFold, Boltz, ESM, or similarYou have MLOps or ML infrastructure experience, particularly with Kubernetes-based training, evaluation, or deployment workflowsYou can define success criteria, validate model quality, and ensure ML releases are robust enough for real-world useYou have led delivery of complex ML projects, including setting technical direction, managing risks and dependencies, and driving teams toward high-quality releasesYou are comfortable operating as a player-coach: mentoring engineers and ML scientists while contributing directly to modeling, experimentation, or architecture when neededYou can work effectively with product, research, leadership, customers, and scientific stakeholders to turn ambiguous requirements into clear technical plansYou have experience with federated learning, privacy-preserving ML, distributed training, or other multi-party training environmentsYou have experience with Go or other systems programming languagesYou have worked on production-grade model delivery in regulated, enterprise, pharmaceutical, biotech, or other high-trust environmentsYou have a publication record in top-tier ML, computational biology, or structural biology venues such as NeurIPS, ICML, ICLR, ISMB, RECOMB, or similarBenefitsIndustry-competitive compensation, including early-stage virtual share optionsRemote-first working – work where you work bestWellbeing budget, mental health support, work-from-home budget, co-working stipend, and learning budgetGenerous holiday allowanceOffice Days at our Berlin HQ or a different European location (3x per year)A high-calibre, execution-focused team with experience from leading organizationsCompany OverviewApheris delivers enterprise-grade AI applications and federated data networks (based on federated learning) for drug discovery It was founded in 2019, and is headquartered in Berlin, Berlin, DEU, with a workforce of 51-200 employees. Its website is https://www.apheris.com.