At Wolfspeed, we do amazing things in a human way.

We know that the achievements of our organization are due to the passion, hard work and creativity of our employees. We celebrate different perspectives to foster excellence across our organization, and our goal is to make diversity a foundation of what we do. We are proudly building an environment where you can bring your authentic self to work.

• Enjoy doing things that people say can’t be done? Innovation is at the center of everything we do.
• Hate red tape? We remove roadblocks instead of creating them.
• Working parent? We provide childcare assistance and paid parental leave.
• Student? We offer continuing education assistance.
• Looking for community? There are many ways to get involved, from Employee Resource Groups to local outreach.

Here’s the Gist (1-2 sentences to summarize the role):

As a Manger of Research Science in Machine Learning you will direct the activities of a research group in the research and/or development of technology relevant to Wolfspeed’s future products, projects and programs. You will collaborate with others on the direction of basic research and development relevant to long-term objectives and concerns and develop strategies to ensure effective achievement of scientific objectives. Additionally, you will oversee interdepartmental activities and research efforts.

The Day-to-Day:

• Lead a team of R&D ML Engineers in deploying enterprise manufacturing solutions to increase revenue and product quality
• Interface regularly across operations, R&D, and IT to develop novel ML techniques for semiconductor manufacturing and development
• Use your previous expertise in AI/ML techniques for computer vision, physics informed ML, and reinforcement learning to mentor early-in-career engineers
• Bring your previous semiconductor/materials science subject matter expertise to discussions

This Job is Right for You if You Have (Minimum Requirements)

• Ph. D. Materials Science, chemical engineering, physics, electrical Engineering, Machine Learning or equivalent degree
• 3-5 years leading an ML team in a high-volume manufacturing setting
• Strong track record of leading cross-functional teams in a dynamic environment
• Prior experience implementing AI solutions into a semiconductor or materials high volume manufacturing environment
• Expertise in dislocation characterization, crystallography, semiconductor device physics and processing
• Expertise in computational modeling of materials systems such as DFT and finite element model Multiphysics simulation

This role may require additional duties and/or assignments as designated by management.