Co-op Fall 2026 - Software Developer, Machine Learning Computer Vision - 4 Months job opportunity at General Dynamics Mission Systems International.

Home Jobs In Canada Tag: Machine Learning Computer Vision - 4 Months Co-op Fall 2026 - Software Developer, Machine Learning Computer Vision - 4 Months position at General Dynamics Mission Systems International


Date2026-05-12T19:47:09.705Z bot
General Dynamics Mission Systems International Co-op Fall 2026 - Software Developer, Machine Learning Computer Vision - 4 Months
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Machine Learning Computer Vision - 4 Months

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degreeGeneral
loacation 1941 Robertson Road, Ottawa, Ontario, Canada
loacation 1941 Robertson..........Canada
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Job DescriptionWe 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.

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