Engineering Group Manager, AI/ML for Chassis Controls

Description

The Role:

Join GM’s Vehicle Mechatronic Embedded Controls (VMEC) team within the Software and Services organization, where we develop and release control software and calibrations that drive the entire vehicle. From internal combustion engines and hybrid drive units to high-voltage batteries and chassis systems, our mission is to invent cutting-edge methods to control the world’s most advanced mechatronic systems.

We are seeking a dynamic and experienced Engineering Group Manager to lead a team focused on Artificial Intelligence (AI) and Machine Learning (ML) solutions for vehicle motion control and estimation. In this role, you will oversee the design, implementation, and optimization of AI/ML-based systems, ensuring they meet performance, scalability, and reliability standards. You will also foster a collaborative, agile environment that empowers innovation and growth. This team works cross-functionally with embedded controls, systems, product, and program teams to deliver high-quality solutions that support GM’s revenue-generating portfolio and accelerate our transition to an all-electric future. As a people leader, you will shape strategic initiatives that align with GM’s transformation from an automaker to a tech-driven company.

What You’ll do:

Lead the development and deployment of AI/ML technologies for GM’s vehicle motion control and estimation.

Collaborate with cross-functional teams, including control engineers, software developers, calibrators, and business stakeholders, to define project requirements and ensure successful execution.

Ensure the timely delivery of projects by monitoring progress, addressing roadblocks, and implementing agile methodologies improve speed, quality, and safety across development cycles.

Provide technical guidance and mentorship to engineers and foster a culture of continuous learning and professional growth.

Stay abreast of emerging technologies and trends in AI/ML, recommending innovative approaches to enhance our designs.

Define system architecture and design, incorporating best practices and industry standards to create robust and maintainable systems.

Communicate project status, risks, and opportunities to senior leadership.

Partner with other departments to promote AI/ML adoption across the organization.

Manage resource planning and team development.

Model and foster GM's Core Values and Winning Behaviors

Your Skills & Abilities (Required Qualifications)

Bachelor of Science degree in Mechanical Engineering, Electrical Engineering, Computer Science, Computer Engineering, Mathematics or a related technical degree

Minimum of 7 years of professional engineering/technical experience

Minimum of 5 years of engineering experience related to AI/ML, control systems, embedded control system, and/or safety critical system development

Strong knowledge of AI/ML concepts, frameworks, and applications in software development.

Experience with common machine learning libraries and frameworks.

Familiarity with deep learning techniques, neural networks, and natural language processing.

Solid understanding of computer programming languages such as Python, Java, C++, etc.

Demonstrated technical background in chassis controls and/or vehicle dynamics

Proven track record of successful project execution

Excellent multi-functional communication and leadership skills - able to get multiple teams moving in the same direction

Demonstrated ability to deal with ambiguity while driving timely decision making

Possess a valid driver’s license and the ability to operate test vehicles

What Will Give You A Competitive Edge (Preferred Skills)

Master of Science in Engineering and/or Master of Business Administration

Master of Science in Electrical, Computer, Mechanical, Mechatronic, Aerospace, Systems or Software Engineering with emphasis in AI/ML, Controls or Robotics

Experience in chassis controls development

Leadership experience developing or applying industry standards

Experience with safety compliance of embedded systems

Leadership of teams of engineers responsible for developing or testing embedded control systems or related hardware in an agile environment

Demonstrated ability to: achieve results through effective teamwork, lead numerous projects with different focal areas to successful completion, and manage and measure work through metrics, data, and results

Experience managing a geographically dispersed global team

Familiarity with embedded controls development tools (e.g. IBM Rational Tool Suite, Jira/Jama, Git ecosystem, MATLAB-Simulink, ETAS)

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area.

The salary range for this role is $ $217,500.00 - 333,400.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.

This job may be eligible for relocation benefits.

About GM

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Why Join Us

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We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

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