Senior Prognostics Data Engineering, Markham, Ontario | General Motors Careers

WORK ARRANGEMENT

Hybrid: This position does not require an employee to be onsite full-time to perform most effectively. The employee’s role enables them to work at the Markham, ON office of General Motors, with the expectation that the employee will be onsite 3 days a week on average.

INTRODUCTION

We are looking for a highly skilled and motivated Senior Prognostics Data Engineer to join our dynamic team. The ideal candidate will have strong technical expertise and play a key role in designing and deploying advanced signal processing methods for prognostics applications. We seek an innovative continuous learner and problem solver, driven to take ideas from concept to production. This is a unique opportunity to work at the forefront of automotive technology and contribute to next-generation prognostics systems.

RESPONSIBILITIES

• Conduct detailed failure mode analysis for vehicle systems to understand potential failure mechanisms.

• Use condition-based monitoring techniques to analyze time-series and sensor data (vibration, temperature, pressure, etc.) using advanced statistical and signal processing techniques.

• Develop and deploy health monitoring models (physics-based and data-driven) to predict potential mechanical system failures and estimate remaining useful life of vehicle components and systems.

• Conduct performance assessment, robustness analysis, validation, and testing through simulation, bench, vehicle, and on-field fleet data.

• Optimize and calibrate signal processing algorithms for efficiency, performance, and scalability.

• Contribute to developing software library and tools for developing predictive maintenance solutions.

• Collaborate with cross-functional teams, including engineering domain experts, product management, and program management to ensure the successful delivery of prognostics products.

• Stay updated on latest advancements, relevant regulations, and standards in prognostics, ensuring compliance in all products and initiatives.

• Communicate technical findings and coach team members, fostering a culture of continuous learning and professional growth.

REQUIRED QUALIFICATIONS

• Degree in Electrical Engineering, Mechanical Engineering, or a related field; PhD is preferred.

• 6+ years of experience in modeling and signal processing techniques (vibration/order analysis, state observer and estimation methods).

• Strong expertise in working with real-world sensor data and digital signal processing fundamentals in time and frequency domains, including time-series analysis, filtering, and spectral analysis.

• Exceptional skills in physics-based/data-driven modeling and signal processing tools (MATLAB, Python, C).

• A passion for continuous learning, technical creativity, and critical thinking to tackle complex challenges and drive advancements in prognostics technology.

• Excellent organizational and problem-solving skills and ability to work in a fast-paced, collaborative, and cross-functional environment.

PREFERRED QUALIFICATIONS

• Expertise in advanced diagnostics, prognostics, or predictive maintenance in the automotive industry.

• Background in systems engineering, including fault tree analysis (FTA), Failure Modes and Effects Analysis (FMEA), and other reliability assessment techniques to identify and analyze potential system failures.

• Experience in robustness analysis, performance assessment and validation, including design of experiments and statistical hypothesis testing.

• Knowledge of vehicle sensors (e.g., wheel speed sensors, accelerometers), vehicle electrical architectures (CAN, Ethernet, etc.), and hands-on experience with tools such as CANalyzer, INCA, Vehicle Spy, and CarSim.

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