Seagate is seeking to advance machine learning capabilities through image-based synthetic data generation for materials science, manufacturing, and metrology applications
Requirements
- Experience with Python and libraries such as OpenCV, PIL, scikit-image, or PyTorch/TensorFlow
- Familiarity with generative AI techniques and image synthesis
- Knowledge of ML model development and evaluation
- Experience with 3D rendering or simulation tools (e.g., Blender, Unity)
- Exposure to materials science or manufacturing domains
- Prior work with image segmentation, classification, or object detection
Responsibilities
- Design and implement pipelines for generating synthetic images using simulation tools and generative models (e.g., GANs, diffusion models)
- Apply image processing techniques to enhance, annotate, and transform raw and synthetic datasets
- Collaborate with ML engineers to integrate synthetic data into model training workflows
- Evaluate the impact of synthetic data on model performance using metrics such as precision, recall, and robustness
- Contribute internal documentation and present findings to cross-functional teams
Other
- Pursuing a PhD degree in Computer Science, Electrical Engineering, Data Science, or related field and must be enrolled in Fall 2026 classes
- Strong communication and collaboration skills
- Travel: None
- Location: Normandale, United States
- Must be available for a 24 to 40-hour-per-week schedule for a full calendar year
