Title :: Machine Learning Engineer
Pay Rate: $84.00/hr
Location: 1 DNA Way, South San Francisco, CA 94080 (Need only local** candidate)
The Role
- You will join Prescient Design within the Computational Sciences organization in gRED. Your peers will be machine learning scientists, engineers, computational chemists, and computational biologists.
- You will closely collaborate with scientists within Prescient and across gRED.
- You will develop machine learning and Bayesian optimization workflows to analyze existing, and design new, small and large molecules.
- You will be expected to form close working relationships with small molecule and protein therapeutic development efforts across the gRED organization.
- You will be expected to work on existing projects and generate new project ideas.
Qualifications:
- PhD degree in a quantitative field (e.g., Computer Science, Chemistry, Chemical Engineering, Computational Biology, Physics), or MS degree and 3+ years of industry experience.
- Demonstrated experience with machine learning libraries in production-ready workflows (e.g., PyTorch + Lightning + Weights and Biases)
- Record of achievement, including at least one high-impact first author publication or equivalent.
- Excellent written, visual, and oral communication and collaboration skills.
Additional desired qualifications:
- Experience with physical modeling methods (e.g., molecular dynamics) and cheminformatics toolkits (e.g., rdkit)
- Previous focus on one or more of these areas: molecular property prediction, computational chemistry, de novo drug design, medicinal chemistry, small molecule design, self-supervised learning, geometric deep learning, Bayesian optimization, probabilistic modeling, statistical methods.
- Public portfolio of computational projects (available on e.g. GitHub).
