AI/ML Process Engineering Intern (Spring 2027)
About The Position
Leading the world’s sustainable energy future, First Solar interns work around the globe/country in research and development, marketing, project development, information technology, engineering, energy services and much more. When you work at First Solar, you will be challenged every day and provided real world experience. You will be given the opportunity to find new solutions and develop new skills to further advance your skillset. At First Solar we strive to foster a culture that encourages innovation through collaboration, urging colleagues to take smart risks, learning from failures and course correcting, and owning personal accountability for contributing to our mission. This internship is expected to last 6 months, spanning the Spring/Summer or Summer/Fall semesters. As an internship company, we allow flexibility to enroll in classes while working as an intern, as long as it doesn’t interfere with the essential functions of the position.
Requirements
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Electrical/Computer Engineering, or a related field; upper-level undergraduate (junior/senior) or graduate student.
- Coursework or project experience applying machine learning to image data (e.g., CNNs, transfer learning) and working proficiency in Python.
- Proficiency in Python and standard ML frameworks (PyTorch, TensorFlow, or scikit-learn).
- Understanding of image classification and transfer learning.
- Basic statistics and experimental design.
- Ability to build and document reproducible data pipelines.
- Strong communication skills to work effectively with an engineer mentor.
Nice To Haves
- Experience with Bayesian optimization or Gaussian Process modeling (e.g., Ax/BoTorch).
- Experience with OpenCV or similar image-processing libraries.
- Materials science/thin-film/photovoltaics background.
Responsibilities
- Build machine-learning tools that support perovskite process development and quality control.
- Train a transfer-learning computer vision model that identifies pinholes, dendrites, and other defects in perovskite device images.
- Build a Gaussian Process surrogate model (Ax/BoTorch) that proposes next experiments for precursor ratio, annealing profile, and coating parameters.
- Present accomplishments and project summary to the leadership team upon completion of the internship.
Benefits
- Real world experience
- Opportunity to find new solutions and develop new skills
- Flexibility to enroll in classes while working as an intern
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What This Job Offers
Career Level
Intern
Education Level
Associate degree
