KLA - AI Vision Engineer

Key Responsibilities : Design, train, and deploy computer vision models for object detection, classification, and positioning in semiconductor service environments.Build robust image and video processing pipelines that handle real-world field conditions.Develop and maintain training data pipelines : collection, annotation, augmentation, and quality assurance.Optimize models for inference performance across deployment targets balancing accuracy, latency, and compute constraints.Integrate vision capabilities into broader multimodal AI systems that combine visual perception with knowledge retrieval and reasoning.Build evaluation frameworks that measure model performance against real field data.Design model architectures that serve both AI knowledge systems and future robotics/automation initiatives.Stay current with the vision model frontier and bring what's relevant into production.Document model architectures, training procedures, and deployment patterns so the team can build on your work. Qualifications : Bachelor's degree in Computer Science, Electrical Engineering, or related field; Master's preferred.1+ years of experience building and deploying computer vision systems (strong new grads with demonstrated projects or research considered).Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).Hands-on experience with object detection and classification architectures and transfer learning / fine-tuning approaches.Experience building training data pipelines annotation tooling, data augmentation, and active learning strategies.Experience with model optimization techniques for edge or constrained deployment.Strong understanding of image processing fundamentals and camera systems.Self-directed you experiment, iterate, and push boundaries without waiting for direction.Excellent problem-solving skills and ability to debug model failures in messy, real-world data.Prior experience in manufacturing, robotics, industrial inspection, or semiconductor environments is a plus.Experience with 3D vision, depth estimation, or point cloud processing is a plus. Key Responsibilities : Design, train, and deploy computer vision models for object detection, classification, and positioning in semiconductor service environments.Build robust image and video processing pipelines that handle real-world field conditions.Develop and maintain training data pipelines : collection, annotation, augmentation, and quality assurance.Optimize models for inference performance across deployment targets balancing accuracy, latency, and compute constraints.Integrate vision capabilities into broader multimodal AI systems that combine visual perception with knowledge retrieval and reasoning.Build evaluation frameworks that measure model performance against real field data.Design model architectures that serve both AI knowledge systems and future robotics/automation initiatives.Stay current with the vision model frontier and bring what's relevant into production.Document model architectures, training procedures, and deployment patterns so the team can build on your work. Qualifications : Bachelor's degree in Computer Science, Electrical Engineering, or related field; Master's preferred.1+ years of experience building and deploying computer vision systems (strong new grads with demonstrated projects or research considered).Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).Hands-on experience with object detection and classification architectures and transfer learning / fine-tuning approaches.Experience building training data pipelines annotation tooling, data augmentation, and active learning strategies.Experience with model optimization techniques for edge or constrained deployment.Strong understanding of image processing fundamentals and camera systems.Self-directed you experiment, iterate, and push boundaries without waiting for direction.Excellent problem-solving skills and ability to debug model failures in messy, real-world data.Prior experience in manufacturing, robotics, industrial inspection, or semiconductor environments is a plus.Experience with 3D vision, depth estimation, or point cloud processing is a plus.