Computer Vision Engineering Intern

JOB DESCRIPTION – Computer Vision Engineering Intern is an industry leading AI company specializing in extracting insights from geospatial big data. Millions of geospatial images are captured every day by satellites, airplanes, and other vehicles - Ecopia converts this flood of pixels into high definition (HD) vector maps, leveraging AI to empower a wide range of decision makers.

As an intern, you will have the incredible experience of working alongside our computer vision and engineering experts. You will receive on-the-job training and an abundance of learning opportunities while working on a graduated deliverable system that will challenge your skills. Full-time employment opportunities are available for successful students.

We are looking for talented self-starting engineers who enjoy diving into a subject and getting their hands dirty. Ecopia is located in the beautiful MaRS Discovery District building at 101 College Street in Toronto. Come join us on the journey to map the world!


Working with the computer vision team to develop scalable algorithms to automatically parse geospatial image data and extract 2D/3D features such as building, roads, parking lot, and addresses at a very large scale

Work alongside the product team to transfer research into new products, new processes, or new business 

- Background in computer science focusing on deep learning and computer vision, or related field
- Solid programming experience in C++/Python
- Demonstrated problem-solving and analytical abilities
- Experience with GPU computing is a plus
- Knowledge of image classification, semantic segmentation, object detection is a plus
- Experience with AWS is a plus

COMMITMENT TO DIVERSITY AND INCLUSION is committed to fostering a diverse and inclusive working environment. We welcome applications from qualified candidates of all backgrounds regardless of age, physical ability, gender, race, religion, and sexual orientation. We will provide any requested accommodation to candidates with disabilities throughout the recruitment process