Principal Machine Learning Scientist

Join BigHat Biosciences, a pioneering company in ML-driven therapeutic antibody design. As a Principal Machine Learning Scientist, you will advance the state of the art in protein engineering, develop and deploy cutting-edge generative models, and contribute to the accelerated design of new therapeutics. You will work closely with an interdisciplinary team and have the opportunity to publish your findings in leading scientific journals.

• Design and implement state-of-the-art generative models of antibody sequence and structure, and predictive models of antibody properties.
• Identify opportunities for improvement in ML tooling, and help to set strategy for ML research, driven by a strong high-level understanding of real-world drug development challenges.
• Develop multi-modality, multi-objective iterative protein sequence optimization approaches to lab-in-the-loop antibody design problems for validation and deployment in our high-throughput wet lab.
• Familiarity with the current state-of-the-art in ML-driven protein engineering
• Strong competency in Python, familiarity with PyTorch, and experience with modern software engineering best practices
• Nice-to-haves include experience with de novo design, NGS data, Bayesian optimization, familiarity with antibody biology and drug development, and experience training and deploying models on AWS
• Publications in major ML conferences and/or leading journals, and an extensive demonstrable track record developing and applying novel ML in industry
• Enjoys a fast-paced environment and excels at executing across multiple projects
• PhD in ML/CS or in the hard sciences with 5+ years experience post-graduation in developing and applying novel ML methods, and a strong quantitative background
• Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams