BigHat Biosciences is seeking a Principal Machine Learning Scientist to advance the state of the art in ML-driven therapeutic antibody design, aiming to accelerate the development of complex, next-generation therapeutics.
Requirements
- PhD in ML/CS or in the hard sciences with 5+ years experience developing and applying novel ML methods and a strong quantitative background.
- Publications in major ML conferences and/or leading journals, or extensive demonstrable track record developing and applying novel ML in industry.
- Strong competency in Python, familiarity with PyTorch, and experience with modern software engineering best practices.
- Familiarity with the current state-of-the-art in ML-driven protein engineering
- experience with de novo design
- experience with NGS data
- experience training and deploying models on AWS.
Responsibilities
- Design and implement the next state-of-the-art generative models of antibody sequence and structure, and predictive models of antibody properties, trained on proprietary internal datasets of thousands to millions of antibodies.
- Identify opportunities for improvement in our ML tooling, and help to set strategy for ML research, driven by a strong high-level understanding of real-world drug development challenges
- Develop, refine, and deploy de novo design methods for generating initial hits to challenging, therapeutically interesting targets.
- 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 - at BigHat success is only declared upon synthesis of real antibodies with drug-like properties.
- Maintain an in-depth understanding of the current state-of-the-art in ML-driven protein engineering, both in the literature and at BigHat.
- Share your findings at top-tier conferences and publish in leading scientific journals to advance the field of protein engineering.
- Provide ML expertise and support for ongoing therapeutics programs, directly contributing to the development of new drugs.
Other
- Provide technical guidance and mentorship to other ML and data science FTEs and interns.
- Collaborate with our engineering team to ensure maximal efficiency in the automated deployment of our latest models to ongoing drug development programs.
- Work closely with an interdisciplinary team of drug developers, wet lab scientists, automation specialists, data scientists, etc. to identify inefficiencies or potential improvements in BigHat’s platform, and plan and prioritize ML methods development accordingly.
- Excellent communication skills, sufficient biomedical domain knowledge to interact effectively with diverse scientific teams.
- Enjoys a fast-paced environment and excels at executing across multiple projects.
