Technical Lead – Structural Biology Networks

🕒 May 4

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Apheris

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2019

🤖 Artificial Intelligence

🧬 Biotechnology

💊 Pharmaceuticals

Artificial Intelligence • Biotechnology • Pharmaceuticals

Apheris is a company that specializes in enabling secure and compliant data collaboration across distributed data environments, particularly for enterprises. The company's solutions empower organizations to engage in federated machine learning and analytics, facilitating the building of models without needing to move sensitive data, thus preserving privacy and security. Apheris focuses on providing technology that allows multi-party data ecosystems and partnerships, with a strong emphasis on compliance, particularly in regulated industries like pharmaceuticals and biotech. Their technology is trusted by major pharmaceutical companies to support AI-driven drug discovery initiatives without compromising proprietary data.

📋 Description

• Lead teams building and delivering federated co-folding models • Build and implement ML applications in structural biology • Own delivery against committed milestones ensuring high-quality model releases • Translate ambiguous scientific and technical goals into clear plans, priorities, and decisions • Guide evaluation decisions and build deliverables for external stakeholders • Surface risks, blockers, and technical trade-offs with clear recommendations • Align consortium members on objectives, evaluation criteria, and delivery expectations

🎯 Requirements

• PhD, MSc, or equivalent experience in a relevant field • 5+ years applying ML to complex scientific or biological problems • Hands-on experience with modern ML systems in Python and PyTorch • Experience with or extended large-scale models such as OpenFold, AlphaFold, Boltz, ESM, or similar • MLOps or ML infrastructure experience with Kubernetes-based workflows • Ability to define success criteria, validate model quality, and ensure robust ML releases • Experience leading delivery of complex ML projects • Comfortable operating as a player-coach: mentoring engineers and ML scientists while contributing directly

🏖️ Benefits

• Industry-competitive compensation, including early-stage virtual share options • Remote-first working – work where you work best • Wellbeing budget, mental health support, work-from-home budget, co-working stipend, and learning budget • Generous holiday allowance • Office Days at our Berlin HQ or a different European location (3x per year)