Senior ML Researcher – Molecular Privacy

This is a fully remote position, open to applicants in Germany.

📋 Description

• Design and implement practical privacy risk experiments using real drug discovery models, linking theoretical threats to realistic attack surfaces.

• Engage directly with molecular and structural ML pipelines (such as protein–ligand models, co-folding architectures, and ADMET / QSAR data) to determine how modeling choices, representations, and uncertainty exploration can reveal sensitive information.

• Develop and modify experimental tools for privacy analysis, including uncertainty probing, generative reconstruction tests, and distributional leakage experiments.

• Create technically credible privacy evidence through hands-on modeling and experimentation, and transform that evidence into clear, informative reports and presentations for consortium and customer decision-makers.

• Convert empirical findings into clear, technically credible privacy narratives for customers, internal stakeholders, and partner organizations.

• Collaborate closely with ML engineers, scientific teams, and other privacy stakeholders to devise mitigation strategies grounded in actual model behavior and implementation constraints.

⛳️ Requirements

• Extensive hands-on experience in building and modifying machine learning models within drug discovery, especially in structure-based modeling and co-folding, with familiarity in related areas such as ADMET.

• Practical experience with privacy in machine learning and/or federated learning, including analyzing privacy risk, model behavior, and governance in distributed or multi-party contexts.

• Proficient in designing empirical privacy experiments and deriving defensible conclusions from both quantitative and qualitative evidence.

• Ability to communicate complex technical risks clearly and credibly to senior scientific, technical, and leadership stakeholders.

• Comfortable managing ambiguous, cross-cutting problems from start to finish, while establishing direction and executing plans.

🏝️ Benefits

• Industry-competitive compensation, including early-stage virtual share options.

• Remote-first working – choose to work where you are most productive, whether at home or a nearby co-working space.

• Comprehensive benefits package, which includes a wellbeing budget, mental health benefits, a work-from-home budget, a co-working stipend, and a learning and development budget.

• Generous holiday allowance.

• Office Days at our Berlin HQ or another European location (three times a year).

• A fun, diverse team of mission-driven individuals with experience from leading organizations and a passion for leveraging AI and ML for positive impact.

• High impact, significant ownership, and the chance to influence how Apheris scales its people and culture during this next growth phase.