Computer Vision, AI (Co-op)

The Computer Vision, AI Co-op will support the development and deployment of AI-driven perception and automated solutions used in real-world operational environments. This role offers hands-on exposure to computer vision, machine learning, data science with a strong focus on practical problem-solving and field validation.

You will work alongside experienced engineers and data scientists to help build, test, and improve intelligent systems that enhance safety, efficiency, and automation. This is an excellent opportunity for students interested in applying AI and automated platforms beyond the classroom in industrial or OT environments.

This Co-op is a 1 year term starting in September.

What You'll Do:

• Assist in developing and testing computer vision models for tasks such as object detection, tracking, and classification


• Support data collection, cleaning, labeling, and exploratory analysis from cameras and other sensors


• Help train, evaluate, and improve machine learning models under guidance from senior team members


• Contribute to integrating AI models, automated platforms, or edge-compute systems


• Participate in in-field testing, validation, and performance evaluation of deployed systems


• Debug issues, reproduce results, and assist with model and software improvements


• Maintain clear documentation and well-organized code to support reliable, reusable solutions

What You'll Bring:

• Currently pursuing an undergraduate or graduate degree in Engineering, Computer Science, Physics, Mathematics, or a related field


• Basic proficiency in Python and familiarity with programming fundamentals


• Exposure to computer vision, machine learning, robotics, or data science concepts through coursework or projects


• Familiarity with common libraries such as NumPy, OpenCV, PyTorch, or TensorFlow (academic or project experience is sufficient)


• Interest in hands-on, applied AI systems and real-world problem solving


• Strong attention to detail, curiosity, and willingness to learn new tools and technologies

Nice to Have:

• Academic or personal projects involving robotics, computer vision, or sensor data


• Exposure to Linux/Unix environments or version control (Git)


• Interest in industrial, automated solutions, or safety-focused applications