Job Description

Machine Learning Research Scientist

Our client is pioneering a new era in drug discovery by leveraging cutting-edge AI foundation models to design molecules. Backed by world-class investors and led by researchers with landmark contributions in AI-for-biology, this team is transforming how medicines are created.

This is not a typical research role. You'll join a small, elite team at a pivotal stage, moving beyond protein structure prediction into real-world therapeutic engineering. On this team, you will directly shape next-generation AI models for antibody and drug design, validated at scale in wet-lab environments.

Responsibilities/Role

• Design and implement novel AI architectures for molecular and protein modeling.
• Translate open-ended biological questions into tractable computational experiments.
• Analyze large-scale biological datasets, define meaningful metrics, and visualize results for diverse audiences.
• Collaborate closely with wet-lab scientists, software engineers, and product teams to iterate rapidly from concept to impact.
• You'll help push the boundaries of AI-driven drug discovery, creating models that could redefine therapeutic design globally.

Qualifications:

• D. or equivalent experience in Machine Learning, Computational Biology, Bioinformatics, Computational Chemistry, or related fields.
• Publications or projects in top-tier ML or life-science venues (e.g., NeurIPS, ICML, Nature Methods).
• Strong Python skills and deep-learning frameworks (PyTorch, TensorFlow).
• Experience training and evaluating large models on protein, antibody, or small-molecule data-or transferable ML expertise.
• Ability to structure complex scientific questions into rigorous modeling workflows.

Job Tags

Similar Jobs