Co-op Fall 2026 Software Developer, Machine Learning Computer Vision 4 Months

We are seeking an analytical and driven Co-op student for a 4-month term to support the development of a standalone AI video analysis tool. This role focuses on the downstream side of a simulation-to-reality pipeline. You will be responsible for ingesting high-fidelity video streams generated by an Unreal Engine 5 vehicle simulator and using that data to train test and refine computer vision models. Your work will directly impact how our AI perceives and interprets complex dynamic environments.

In this position you will work closely with the simulation team to define the ground truth requirements needed for effective model training. You will develop scripts and workflows to process synthetic datasets ensuring that the exported entities from the simulation are correctly mapped to your training architecture. This includes handling tasks such as object detection classification and tracking. You will evaluate model performance against the simulated data identifying edge cases where the AI struggles and providing feedback to the simulation developers to help generate more robust training scenarios.

This role offers a unique opportunity to work with synthetic data generation a cutting-edge field in machine learning that bypasses the limitations of manual data labeling. You will gain practical experience in building a modular AI toolset that can be validated in a controlled virtual environment before moving toward real-world applications. It is an ideal placement for a student looking to bridge the gap between theoretical machine learning and practical systems-level integration.

Qualifications :

Key Qualifications

• Academic Background: Currently pursuing a degree in Computer Science Data Science Mathematics or an Engineering discipline with a focus on Artificial Intelligence.
• Machine Learning Fundamentals: A solid understanding of core ML concepts particularly in Computer Vision (e.g. CNNs object detection frameworks like YOLO or SSD).
• Programming Proficiency: Strong skills in Python including familiarity with libraries such as OpenCV NumPy and PyTorch or TensorFlow.
• Data Pipeline Interest: An interest in learning how to handle large datasets and automate the preprocessing of video frames and metadata.
• Analytical Mindset: Ability to interpret model metrics (precision recall mAP) and troubleshoot why a model may be underperforming in specific simulated conditions.
• Collaborative Spirit: Strong communication skills to help coordinate data formats and synchronization requirements with the Unreal Engine development team.
• Bonus Points: Previous experience with Docker Linux environments or an interest in synthetic data/Sim2Real challenges.

It is a requirement that General Dynamics Mission SystemsCanada be registered with the Canadian Controlled Goods program and that all of its workforce be security assessed. Successful applicants must meet all applicable security requirements including but not limited to the ability to obtain and maintain a Canadian government security clearance. Applicants may be required to meet additional security requirements in order to gain access to technical data classified areas or information that is subject to international regulations. You must be eligible to work in Canada.

Additional Information :

Compensation 
The expected hourly rate for this position is $21.20 $33.23. Final compensation will be determined based on your relevant work experience to date. As part of student placement you will be eligible for quarterly pay increases.

Why Students Love Working Here

• Purposeful Innovation & Problem Solving: Youll work alongside experienced professionals and some of the brightest minds in the defence sector gaining hands-on experience with next-generation technologies. This is a place where your ideas are encouraged creativity is valued and youll be supported as you learn and help drive modern practical solutions.
• Connection & Mentorship: Through onboarding to your career journey with us you will work with teammates that are excited to share their experience and develop your skills. Have meaningful interactions ask questions and build relationships that can lead to lasting industry connections.
• Perks & Highlights:
  • Eligibility for future co-ops or full-time roles
  • Flexible work hours and compressed workweek options
  • Hybrid work model (where applicable)
  • Networking opportunities across teams and disciplines
  • Onsite amenities and social events (gym bike storage trivia appreciation events etc.)
  • Corporate discounts

Accommodation 
If you require accommodation during any stage of the application process please contact Human Resources via .

Remote Work :

No

Employment Type :

Intern