Work Arrangement:
This role is categorized as hybrid. This means the successful candidate is expected to report to Mountain View, CA three times per week at minimum or other frequency dictated by the business or Remote, Washington or California state location.
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.
What You'll Do
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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.
Your Skills & Abilities (Required 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).
What Will Give You a Competitive Edge (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.
Company Vehicle : Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.
This Job may be eligible for relocation benefits.
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