ML Research Scientist, Co-Folding and Affinity

The ML Research Scientist, Co-Folding and Affinity will develop and iterate deep learning models for protein-ligand co-folding and structure prediction, benchmark model performance against state-of-the-art methods, and contribute to research-to-product pipelines in SandboxAQ's drug discovery workflows. Responsibilities include implementing and refining co-folding models, designing systematic evaluation pipelines, collaborating with ML engineers and structural biologists to scale models into production-ready workflows, and communicating findings through internal talks and publications. Required expertise includes a Ph.D. in a relevant field, hands-on experience with protein structure prediction methods (e.g., AlphaFold2/3, RoseTTAFold), proficiency in Python and ML frameworks (PyTorch and/or JAX), and a track record of rigorous experimental design and collaboration. Highly desired candidates have postdoctoral experience in co-folding or structure-based drug design, familiarity with binding affinity prediction, publications in leading venues, and cloud-verse implementation experience. SandboxAQ offers competitive compensation, comprehensive benefits, flexible work arrangements, and ongoing career development.