2027 Summer Intern, Fleet Reliability & Test Engineering, ASD

General Motors•Milford, MI

8d•$8,100 - $8,700•Onsite

About The Position

The Autonomous Vehicle (AV) Engineering organization supports the development of safe, reliable, and high-performing assisted and automated driving systems throughout the vehicle lifecycle. Our teams combine vehicle systems expertise, engineering analysis, data, hands-on execution, and disciplined documentation to accelerate learning and enable productive development testing. The Fleet Reliability Engineering and AV Test Engineering teams work closely with AV Operations, Service Operations, technicians, vehicle integration, software, systems, safety, and supplier teams. Together, they identify risks, plan and execute validation, analyze vehicle and fleet performance, resolve issues, and improve the processes that keep development vehicles safe, available, serviceable, and ready for testing. We are hiring interns across two complementary focus areas. Both opportunities offer hands-on experience with autonomous vehicle development, cross-functional problem-solving, data analysis, scripting, and real-world engineering execution.

Requirements

Strong interest in autonomous vehicles, vehicle systems, reliability, diagnostics, testing, embedded systems, simulation, data analysis, or related areas.
A hands-on mindset—you enjoy building, testing, troubleshooting, debugging, analyzing, and learning through doing.
Excellent problem-solving skills and attention to detail.
Ability to communicate technical findings clearly, both verbally and in writing.
Comfort working collaboratively in a team environment and managing multiple tasks toward a deliverable.
Pursuit of a bachelor’s degree in Computer Science or Engineering, including Electrical, Computer, Mechatronics, Systems Design, Mechanical, Chemical, or an equivalent discipline.
Coursework or project experience in Python, MATLAB, or embedded microcontrollers.
Ability to work full time, 40 hours per week.

Nice To Haves

Basic understanding of automotive control systems, ADAS features, vehicle diagnostics, sensors, electronics, vehicle testing, fleet operations, or software validation.
Familiarity with reliability methods, root-cause analysis, data analysis, model-based design tools such as MATLAB/Simulink, simulation, HIL/SIL, data logging, or test automation.
Familiarity with automotive communication protocols such as CAN, LIN, or Ethernet.
Proficiency in scripting or data-analysis languages such as Python, MATLAB, or SQL.
Experience developing engineering tools, dashboards, automated workflows, test datasets, or regression suites.
Intent to return to a degree program after completion of the internship.
Expected graduation between December 2027 and August 2028.

Responsibilities

Define and improve fleet health, reliability, availability, uptime, and serviceability metrics.
Analyze vehicle health data, telemetry, diagnostic information, service records, work orders, incidents, and operational data.
Support dashboards, data-mining activities, and analytics that provide visibility into fleet condition and reliability trends.
Investigate recurring vehicle, hardware, software, sensor, electrical, or operational issues by organizing symptoms, timelines, configurations, and supporting evidence.
Support root-cause investigations, issue prioritization, corrective-action tracking, and communication of findings to technical and operational stakeholders.
Partner with technicians and service teams to evaluate repairs, maintenance activities, return-to-service requirements, and opportunities to improve repeatability.
Develop standard work, checklists, troubleshooting guides, and documentation that improve fleet reliability, service execution, and issue closure.
Develop scripting and analysis tools to automate data processing, fleet reporting, reliability calculations, and engineering workflows.
Support reliability testing and validation activities using vehicles, benches, diagnostic tools, simulation, and available fleet data.
Translate engineering questions, feature requirements, and test requests into clear test cases, procedures, and acceptance criteria.
Assess test feasibility and identify dependencies, including vehicles, routes, prototypes, software branches, tools, instrumentation, safety coverage, staffing, and operating approvals.
Prepare and execute feature, sensor-level, system-level, regression, A/B comparison, and vehicle-level tests.
Execute performance and validation tests using simulation, playback, bench, HIL/SIL, closed-course, and on-road fleets.
Develop scripts to automate testing, data collection, result processing, and repeatable test workflows in vehicles and on benches.
Analyze vehicle, sensor, software, and system data to evaluate performance, identify regressions, and improve validation efficiency.
Document test results, consolidate findings, create defects or mitigations, and support root-cause investigations and re-test plans.
Support the creation of test datasets, scenario libraries, regression suites, dashboards, and automated test pipelines.
Coordinate with AV Operations and cross-functional engineering teams to schedule and execute testing safely and consistently.
Collaborate with cross-functional engineering and operations teams to deliver technical work and improve AV development processes.
Apply structured problem-solving to organize technical evidence, identify trends, and recommend next steps.
Prepare technical summaries and communicate findings clearly to technical and operational stakeholders.
Draw in senior engineers or technical experts when needed.
Manage multiple tasks while maintaining attention to detail and working toward defined deliverables.