Product Manager, Materials Science AI and Machine Learning
About this role
This role is suited for an experienced manager who has successfully led scientific research projects and collaborations, particularly within the machine learning domain. The individual will be responsible for managing the development of AI and ML products within the Materials Science team at Schrödinger. This involves leveraging deep domain knowledge in chemistry and machine learning to expand the company's offerings across various industries such as aerospace and consumer goods. The position exists to drive the growth of the materials discovery platform by connecting scientific research with software solutions.
The ideal candidate is an extrovert who enjoys engaging with customers and presenting findings publicly. They should also possess expertise in agentic workflows and strong communication skills to guide product strategy. This role requires someone who can bridge the gap between complex materials science concepts and actionable ML product development roadmaps.
What you will do
- Interface with current and prospective customers to demonstrate how the software accelerates materials science research.
- Provide guidance and roadmap planning necessary to expand current offerings into new areas of materials science.
- Develop novel machine learning models to support the acquisition of new customers.
- Manage the existing Materials Science ML team effectively.
- Collaborate on the overall strategy for the Materials Science ML product line.
What you need
- A PhD in Materials Science, Computational Chemistry, Chemical Engineering, Artificial Intelligence, or a related field is required.
- Candidates must possess practical experience in both Materials Science and Machine Learning.
- Demonstrated experience working within the software industry and interacting with customers is necessary.
- A strong background in both MS and ML is essential for success in this role.
- Experience leading scientific research projects and collaborations in the ML space is a key qualification.
Nice to have
- Experience with agentic workflows
Benefits
- Competitive salary
- Equity-based compensation
- Healthcare (with dental and vision)
- 401k
- Pre-tax commuter benefits
- Flexible work schedule
- Parental leave program
- Over a month of paid vacation time
Skills and tech stack
Questions candidates ask
What is the typical compensation range for this role?
The estimated base salary range for this position is $200,000 to $275,000. The actual compensation package is dependent on various factors, including experience and education.
What is the remote policy?
Schrödinger has teams all over the world, with the largest office located in New York. The posting does not specify a general remote policy for this role.
What is the team structure like?
The role is within the Materials Science (MS) Machine Learning (ML) team. The team size is not specified in the posting.
What is the hiring process?
If you have questions regarding compensation, candidates should reach out to a member of the Strategic Growth team.