Senior ML Research Engineer

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

📋 Description

• Design and enhance machine learning models in the fields of molecular and structural biology, including co-folding and binding affinity models, tailored for drug design applications and workflows.

• Lead the development process of models from initial concept through multiple prototyping phases to create robust tools.

• Establish benchmarking and evaluation strategies to assess model performance.

• Continuously iterate and refine modeling techniques driven by data insights.

• Identify and resolve data quality and pipeline issues that impact model performance.

• Keep up-to-date with the latest research and identify effective public methodologies for research and development.

• Collaborate with clients, partner-facing engineers, and external collaborators to facilitate real-world drug design applications.

• Implement research projects and translate scientific objectives into cutting-edge ML models that are evaluable, deployable, and applicable in drug discovery workflows.

⛳️ Requirements

• PhD or MSc in machine learning, computational biology, computational chemistry, bioinformatics, physics, or a related discipline.

• Minimum of 2 years of professional experience applying machine learning techniques to scientific challenges.

• Practical experience in training, fine-tuning, and extending deep learning models for molecular or protein structure modeling.

• Proficient in critically analyzing ML models, their training processes, and scientific benchmarks, translating findings into meaningful enhancements.

• Expertise in Python and PyTorch.

• Capable of producing clean and reliable code.

• Familiarity with multi-GPU and distributed training environments.

• In-depth knowledge of structural biology and protein-ligand data formats, including quality metrics and tools.

• Proactively seek out opportunities to contribute scientifically to achieve organizational objectives.

• Preferred: experience in federated learning, privacy-preserving ML, or secure model training.

• Preferred: experience in developing ML models for drug design within pharmaceutical or biotech settings.

• Preferred: publications in leading ML or structural biology venues or contributions to open-source projects in related fields.

🏝️ Benefits

• Competitive industry compensation, including early-stage virtual share options.

• Remote-first working environment – work from wherever you are most productive, whether at home or in a nearby co-working space.

• Wellbeing budget.

• Mental health benefits.

• Work-from-home budget.

• Co-working stipend.

• Learning and development budget.

• Generous holiday allowance.

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