Job Description

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

• 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).

• 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.

• System Integration: Oversee the integration of AI pipelines with foundational infotainment operating systems, particularly Android Automotive OS (AAOS) and QNX.

• Cross-Functional Strategy: Partner with product managers, data scientists, and hardware engineers to balance feature ambition with compute constraints.

• 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.

• Prototyping: Rapidly prototype new AI concepts and evaluate emerging frameworks to keep GM at the cutting edge of automotive technology.

Minimum Qualifications

• Experience: 10+ years of professional software engineering experience, with at least 3+ years in a technical leadership or architectural role.

• Programming: Expert-level proficiency in modern C++ (C++14/17/20) and Python.

• Domain Expertise: Proven track record of shipping commercial software in automotive infotainment, robotics, consumer electronics, or other deeply embedded systems.

• AI/ML Deployment: Hands-on experience optimizing and deploying ML models to edge hardware (NPU/GPU/DSP utilization, quantization, pruning).

• OS Knowledge: Deep understanding of POSIX-compliant operating systems, Linux internals, or RTOS (QNX, VxWorks).

• Education: Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field (or equivalent practical experience).

Preferred Qualifications

• Extensive experience with Android Automotive OS (AAOS), specifically Vehicle HAL (VHAL) and native C++ services.

• Experience building or integrating advanced Voice Assistants (ASR, NLU, TTS) or Driver Monitoring Systems (DMS) into embedded environments.

• Familiarity with automotive functional safety standards (ISO 26262, ASIL) and cybersecurity protocols.

• 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.





This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.

This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.



About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

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