General Motors-posted 29 days ago
Full-time • Mid Level
Onsite • Warren, MI
5,001-10,000 employees
Transportation Equipment Manufacturing

At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We're turning today's impossible into tomorrow's standard -from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. We are seeking a Senior Engineer, AI Systems Engineering - Optimization to join our Manufacturing Technology Development team within the General Motors Research and Development organization. In this role, you will design breakthrough optimization strategies for compute, memory, and energy in robotic systems. You will experiment with neural compression, hardware-software co-design, and real-time algorithm tuning. You will collaborate with AI & Simulation to harden new AI models and with Robotics Intelligence to ensure advanced algorithms can run on constrained platforms.

  • Design optimization strategies for compute, memory, and energy efficiency.
  • Experiment with neural compression and algorithm tuning.
  • Collaborate with AI & Simulation to harden AI models.
  • Ensure real-time performance on constrained platforms.
  • Develop co-design frameworks for hardware and software.
  • Contribute to system-level performance improvements.
  • 5+ years of experience in optimization for AI and robotics systems.
  • Strong background in neural compression and embedded AI.
  • Experience with hardware-software co-design.
  • Bachelor's degree in Electrical Engineering, Computer Science, or related field.
  • Proven ability to improve system performance.
  • Master's or PhD in AI, Robotics, or related field.
  • Experience with real-time systems and constrained platforms.
  • Track record of innovation including patents or publications.
  • Knowledge of energy-efficient computing.
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