Technical Lead – Large Molecule AI Systems

🕒 May 27

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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 large molecule AI systems, staying hands-on across antibody modeling, co-folding, binder prediction, and developability • Build and implement ML applications large biomolecular foundation models such as OpenFold, Boltz-2 and ESM • Own delivery of these against committed milestones and ensure high-quality model releases ship on time • Translate 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 stakeholders • Surface risks, blockers, bugs, timeline changes, and technical trade-offs early, with clear recommendations • Align consortium members on objectives, evaluation criteria, data requirements, timelines, and delivery expectations • Work with product, engineering, research, and leadership to ensure application requirements shape the model roadmap.

🎯 Requirements

• PhD, MSc, or equivalent experience in a relevant field • 5+ years applying ML to complex scientific or biological problems, ideally in structural biology, antibody engineering, biologics discovery, developability prediction, binder prediction or protein design • Hands-on experience with modern ML systems in Python and PyTorch • Worked with or extended large-scale models such as OpenFold, AlphaFold, Boltz, ESM, or similar • MLOps or ML infrastructure experience, particularly with Kubernetes-based training, evaluation, or deployment workflows • Define success criteria, validate model quality, and ensure ML releases are robust enough for real-world use • Led delivery of complex ML projects, including setting technical direction, managing risks and dependencies, and driving teams toward high-quality releases • Comfortable operating as a player-coach: mentoring engineers and ML scientists while contributing directly to modeling, experimentation, or architecture when needed • Work effectively with product, research, leadership, customers, and scientific stakeholders to turn ambiguous requirements into clear technical plans.

🏖️ 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) • A high-calibre, execution-focused team with experience from leading organizations