QA Engineer - Machine Learning

General Motors is transforming the future of mobility and the Canadian Technical Centre (CTC) is at the forefront of that transformation. We are a diverse team of agile and innovative thought leaders who are passionate about developing key technologies and products that will help achieve GMs vision of a world with Zero Crashes Zero Emissions and Zero Congestion.
CTC has a proven track record of taking technologies from concept to production in both automotive and non-automotive areas. Our success is propelled by our talented people and our deep technical knowledge in domains like infotainment software diagnostics data analytics AI and mechatronic controls. As part of Software Test Engineering for Autonomous Vehicle Integrity Platform (AVIP) Diagnostics QA team you will be part of fast-paced agile teams building software and innovative solutions in the ADAS and Autonomous domain. Software Test Engineering ensures applications meet GM software and feature standards for functional system quality performance and architecture requirements. Ability to drive advanced levels of test planning execution and quality reporting of software applications through engagement with software developers system stakeholders and sustaining/integration groups. This includes the creation and implementation of both automated and manual test cases and test execution plans.

Develop and execute comprehensive test plans test cases and test scripts (unit bench and in-vehicle as needed) for new and existing software features
Investigate issues and drive continuous improvement of processes products methodologies and innovation
Collaborate with Software and Systems Engineers in architecting requirements and design reviews
Create test cases that can be executed manually when necessary but designed and optimized to be automated; ability to write accompanying automation scripts using industry-standard tools and coding methodology
Execute manual and automated tests troubleshoot script and test environment issues triage and log defects and track progress to plan.
Review test plans test cases and automation scripts designed by others and provide insightful feedback/assistance
Average travel requirements of 2-3 weeks a year including travel to the US
Bachelors or Masters degree in Computer Science Mechatronics Software Engineering Electrical Engineering Computer Engineering or related fields

• 3 years of embedded software development and test experience in C and C
• Solid knowledge of software testing methodologies and tools
• Technical knowledge of ADAS system software
• Proficiency in Python programming and other languages (e.g. Strong experience with test automation framework (e.g. Creative disciplined strong sense of responsibility
• Understanding of major automotive vehicle systems such as Advanced Driver-Assistance (ADAS) Motion Control Automotive Network and Powertrain and their associated Diagnostics

Experience with OBDII ISO26262 functional safety control systems and ISO14229
Experience with Machine/Deep Learning algorithms
Exposure to Automotive Platforms (Ethernet/CAN/LIN AUTOSAR)
Knowledge of vehicle architectures serial data communication and hardware/software interfaces.

GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILLNEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE.

Paid time off including vacation days holidays and supplemental benefits for pregnancy parental and adoption leave.
Healthcare dental and vision benefits.
Life insurance plans to cover you and your family.
Company and matching contributions to a Defined Contribution Pension plan to help you save for retirement.
General Motors is committed to being a workplace that is not only free of unlawful discrimination but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.
General Motors offers opportunities to all job seekers including individuals with disabilities.