Hybrid Summer Intern: System Safety & AI Validation

General Motors Corporation

Warren (MI)

Hybrid

USD 30,307,000 - 41,328,000

Full time

4 days ago
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Job summary

General Motors Research & Development invites applications for a 2027 Summer Intern – System Safety. This role supports research, safety analysis, and the development of safety cases for safety-critical systems across engineering and AI/ML domains.

The intern will collaborate with multiple teams to align claims with standards (UL 4600, ISO 26262, ISO 21448, AI safety) and help ensure evidence-based decision-making throughout the product lifecycle. Hybrid work in Warren, MI is expected.

Qualifications

  • Pursuing an advanced degree in a technical field (MS/PhD).
  • Current student eligible for full-time summer internship.
  • Experience in systems engineering or safety-related environments is beneficial.
  • Knowledge of safety standards (ISO 26262/21448/8800) is a plus.

Responsibilities

  • Conduct research and develop safety analyses and system safety cases for complex products.
  • Assess evidence strategies and sufficiency criteria to support safety arguments.
  • Prepare safety-case materials for product submissions, audits, and regulatory audiences.
  • Collaborate with AI/ML, cybersecurity, validation, and product safety teams to strengthen traceability and evidence quality.
  • Identify gaps and risks, surface safety gaps, and escalate appropriately.

Skills

Systems engineering
Safety assurance
Technical communication
Analytical thinking

Education

MS or PhD candidate in Engineering/CS/Math/Robotics/Safety Management
Current student

Tools

GSN

Job description

General Motors Research & Development invites applications for a 2027 Summer Intern – System Safety. This role supports research, safety analysis, and the development of safety cases for safety-critical systems across engineering and AI/ML domains.

The intern will collaborate with multiple teams to align claims with standards (UL 4600, ISO 26262, ISO 21448, AI safety) and help ensure evidence-based decision-making throughout the product lifecycle. Hybrid work in Warren, MI is expected.

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