Jobs at General Motors in Canada

Work Arrangement: This role is Hybrid at Oshawa Elevation Centre, and you are expected to report to that location at least three times a week.

At General Motors, we envision a future characterized by zero crashes, zero emissions, and zero congestion. We are pioneering the next generation of vehicle compute platforms and revolutionizing automotive software development.

Join us as we lead the way towards a sustainable and safe automotive future.

We are seeking a talented Senior Software Developer with expertise in vision systems to join our dynamic engineering team.

The Role

We are looking for a skilled Senior Software Developer with a deep understanding of developing software and algorithms for real-world customer-facing features and systems. The ideal candidate will have a strong background in software development (C/C++) in a scrum/agile environment, a passion for innovation, and experience with systems applications using both classical and machine learning-based computer vision methodologies.

The successful candidate will join the vehicle camera team and will take broad responsibility for advanced technologies development and productization, as well as safety applications, from algorithmic proof of concept to deployment in core technologies within the infotainment system on the vehicle.

What You'll Do (Responsibilities)

• Design, implement, test, and maintain embedded software and algorithms using various technologies.

• Work in a multinational organization to explore, develop, and productize vehicle camera technologies focused on safety applications, in-vehicle customer-facing video applications, and vehicle camera backend services.

• Contribute to the creation of core vision system technologies, utilizing both classic and advanced techniques, with an emphasis on data-driven development, debugging, and deployment on embedded systems with challenging compute and runtime requirements.

• Develop technology solutions based on product needs, exploring various algorithm methods (classic, learned, etc.), acquiring necessary data and simulation environments, and progressing to implementation and integration with embedded targets, considering computational and real-time constraints.