AI Vision Engineer

Role Overview

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.

What You Will Do

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.

Why It Might Be a Fit

Self-directed, 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.

Requirements

• 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 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

Benefits

• Competitive, family friendly total rewards package
• Inclusive environment
• Benefits that meet the diverse needs of employees