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About This Role
Job Description
About the Team:
GM’s Autonomous Vehicle Platform Software Engineering organization builds the foundational software that enables autonomous-driving capabilities to run reliably on production vehicle platforms. The organization’s teams span platform operating systems and compute drivers, embedded MCU software, core services and tools, and system-performance engineering. Their work includes developing low-level platform software, middleware, service interfaces, software-update and deployment capabilities, diagnostics, logging and observability, and performance tooling across vehicle compute systems.
Working at the intersection of software, hardware, AI/ML, and vehicle systems, the teams integrate operating systems, sensors, compute, and application workloads to deliver secure, efficient, testable, and production-ready autonomous-vehicle capabilities. Engineers collaborate closely with AV, AI/ML, hardware, systems, validation, and safety partners, with opportunities to contribute across embedded software, platform engineering, developer tools, and performance optimization. Depending on team needs, projects may focus on platform OS and drivers, MCU software, core services, vehicle software integration, or system and ML-workload performance.
About the Role:
As an Autonomous Driving Software Engineer Intern, you will contribute to the design, development, and validation of cutting-edge software powering self-driving systems. You’ll collaborate with experienced engineers across AV Platform teams to build scalable, safety-critical software for autonomous vehicles operating in real-world environments.
What You’ll Do:
- Develop, test, and deploy production-ready code across components of vehicle platform software.
- Quickly ramp up on assigned codebase, product area, and/or system.
- Complete assigned tasks efficiently with few iterations.
- Identify problem statements, outline optimal solutions, account for tradeoffs and edge cases
- Participate in design reviews, code reviews, technical discussions, and continuous integration and deployment practices.
- Collaborate with cross-functional teams including hardware, systems, test, and safety to ensure seamless software integration.
Communicate effectively across multiple stakeholders.
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Required Qualifications:
- Currently enrolled in a full-time, degree-seeking program and in the process of obtaining a Bachelor's or Master's degree in computer science, artificial intelligence, machine learning, robotics, engineering, or a related STEM field.
- Must be graduating between December 2027 and August 2029 and have at least one additional quarter/semester of school remaining following the completion of the internship.
- Availability to work full-time, 40 hours per week, during the 12 week summer internship period between May 24th – August 13th or June 14th – September 3rd 2027
- Strong foundation in algorithms and data structures, with proficiency in C++, Python, or another object-oriented programming language.
Strong written and verbal communication skills and the ability to collaborate across teams.
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Preferred Qualifications
- Demonstrated software engineering experience through an internship, work experience, coding competition, student engineering team or competition (e.g., SAE student competitions, EcoCAR, Formula SAE, or Baja SAE), research, coursework, or personal project.
- Experience building, testing, and shipping production software, with exposure to safety-critical development (FDA, FAA, Automotive)
- Familiarity with embedded build systems such as Yocto or Buildroot, networking fundamentals, and software integration across compute, MCU, and vehicle platforms.
- Understanding of networking fundamentals relevant to embedded or distributed systems.
- Experience with robotics frameworks (e.g., ROS), embedded Linux platforms, or common sensors (e.g., cameras, lidar, radar, IMUs) is a plus.
Passion for self-driving technology and its potential impact on the world
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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 New York, Colorado, California, or Washington.
- The salary range for this role is $8,100 – $10,300 per month. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
- GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2027 Student Program - to help facilitate administration of relocation benefits, please apply using the permanent address you would move from.
Work Arrangement:
Hybrid : This role is categorized as hybrid. This means the successful candidate is expected to report to their designated office three times per week, at minimum.
Location:
- Sunnyvale, California
- Warren, Michigan




 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
General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.
Salary Context
This $97K-$123K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $192K across 146 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 8,943 AI roles we're tracking, AI Software Engineer positions make up 4% of the market. At General Motors (GM), this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,448 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $110,408. This role's midpoint ($110K) sits 50% below the category median. Disclosed range: $97K to $123K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
General Motors (GM) AI Hiring
General Motors (GM) has 7 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer, AI Product Manager. Positions span Sunnyvale, CA, US, Warren, MI, US, Austin, TX, US. Compensation range: $115K - $333K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (175) are outnumbered by mid-level (4,132) and senior (3,268) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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