General Motors

HQ
Detroit
Total Offices: 9
165,000 Total Employees
Year Founded: 1908

General Motors Offices

General Motors is headquartered in Detroit and has 9 office locations.

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

Roles that are categorized as Hybrid mean that the successful candidate is expected to report onsite to the designated facility at least three times per week or other frequency as dictated by the business.

Typical time on-site: 3 days a week

U.S. Office Locations

HQ
Detroit

Hudson's Detroit building Global HQ

At Hudson’s Detroit, GM teams build on more than a century of automotive expertise to drive the next chapter in automotive history.

Austin

Austin IT Innovation Center

The spirit of boldness, creativity and ambition lives and breathes in the city of Austin, home to one of our innovation centers. Here our IT team members support GM's IT needs in developing web technologies, end-user applications, dealer and factory systems and vehicle technology.

Concord

Charlotte Technical Center

7605 GM One Team Dr NW, Concord, NC, United States, 28027

Los Angeles

Los Angeles, CA, United States

Milford

3300 General Motors Road, Milford, MI, United States, 48380

Mountain View

Mountain View Tech Center

Opened in 2024, our Mountain View facility serves as a hub for research and innovation in Silicon Valley. Designers, engineers, and staff at this state-of-the-art campus support the advancement of General Motors’ product portfolio through software development, engineering and design.

Pasadena

Advanced Design and Innovation Campus

The teams at the General Motors Advanced Design and Innovation campus in Pasadena, CA, are charged with exploring future transportation, technology and consumer trends and creating conceptual mobility solutions that inspire and inform program teams across the company.

Pontiac

Pontiac Engineering Center

The Pontiac Engineering Center (PEC) is a hub for propulsion testing, validation and pre-production operations for fuel cell, electrification, engines, and transmissions. The campus is also home to our Performance and Racing Center, which includes design, build and test of race engines.

Warren

Global Technical Center

The General Motors Global Technical Center is globally recognized as the preeminent innovation center for automotive engineering, design, and advanced technology.

11 Days AgoSaved
Hybrid
Westlake Village, CA, USA
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Provides administrative, operational, financial, facilities, and event coordination support for regional sales leadership. Responsibilities include managing calendars, travel, expenses, invoices, purchase orders, meetings, office workflows, technology support, interviews, onboarding, and regional engagement activities. The coordinator supports multiple leaders, maintains confidentiality, tracks spending, resolves issues, and collaborates with Sales Support, HR, Finance, IT, and other regional teams.
2 Days AgoSaved
Remote or Hybrid
United States
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Leads the strategy, validation, and safety assurance of Level 3–4 autonomous driving behaviors powered by machine learning. Owns behavior-related safety cases, standards alignment, ODD and evaluation frameworks, safety metrics, launch-readiness assurance, and evidence assessment across simulation, closed-course, and public-road testing. Leads cross-functional technical collaboration and builds a high-performing AV behavior safety engineering team through hiring, coaching, and development.
2 Days AgoSaved
Remote or Hybrid
United States
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Design, develop, and operate governed feature engineering pipelines and a shared feature platform for machine learning and advanced analytics. Build scalable transformations using Python, SQL, Spark, and Databricks; establish feature reuse, versioning, train-serve parity, data quality controls, CI/CD, monitoring, and documentation. Collaborate with data scientists, ML engineers, data engineers, and platform teams to deliver reliable production features and resolve pipeline issues.