The Role
As a Principal Software Engineer in the Vehicle AI division, you will be the technical cornerstone of our smart cabin initiatives. You will architect, design, and deploy low-latency, high-performance AI software that runs directly on edge hardware within the vehicle.
You won't just be writing code; you will define the technical roadmap, mentor senior engineers, and collaborate across hardware, UI/UX, and vehicle software teams to bring intelligent features—like natural language voice assistants, driver monitoring systems (DMS), and predictive cabin personalization—to life.
Key Responsibilities
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Architectural Leadership: Design scalable, secure, and real-time software architectures for AI-driven features running on automotive-grade compute platforms (e.g., Qualcomm Snapdragon Digital Chassis, NVIDIA DRIVE).
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Edge AI Optimization: Lead the deployment and optimization of machine learning models (LLMs, computer vision, audio processing) for resource-constrained edge devices using TensorRT, ONNX, or similar frameworks.
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System Integration: Oversee the integration of AI pipelines with foundational infotainment operating systems, particularly Android Automotive OS (AAOS) and QNX.
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Cross-Functional Strategy: Partner with product managers, data scientists, and hardware engineers to balance feature ambition with compute constraints.
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Mentorship & Excellence: Elevate the engineering culture by establishing best practices for code quality, CI/CD, rigorous testing, and system performance profiling. Set the standard for technical excellence within the division.
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Prototyping: Rapidly prototype new AI concepts and evaluate emerging frameworks to keep GM at the cutting edge of automotive technology.
Minimum Qualifications
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Experience: 10+ years of professional software engineering experience, with at least 3+ years in a technical leadership or architectural role.
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Programming: Expert-level proficiency in modern C++ (C++14/17/20) and Python.
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Domain Expertise: Proven track record of shipping commercial software in automotive infotainment, robotics, consumer electronics, or other deeply embedded systems.
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AI/ML Deployment: Hands-on experience optimizing and deploying ML models to edge hardware (NPU/GPU/DSP utilization, quantization, pruning).
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OS Knowledge: Deep understanding of POSIX-compliant operating systems, Linux internals, or RTOS (QNX, VxWorks).
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Education: Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field (or equivalent practical experience).
Preferred Qualifications
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Extensive experience with Android Automotive OS (AAOS) , specifically Vehicle HAL (VHAL) and native C++ services.
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Experience building or integrating advanced Voice Assistants (ASR, NLU, TTS) or Driver Monitoring Systems (DMS) into embedded environments.
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Familiarity with automotive functional safety standards (ISO 26262, ASIL) and cybersecurity protocols.
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Advanced degree (Master’s or Ph.D.) focusing on Artificial Intelligence, Machine Learning, or Embedded Systems.
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 (238,000 and 365,000). The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.
