Staff AI ML Engineer
General Motors
Job Overview
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Job Description
About the Role
We are seeking an experienced Staff full stack engineer with a strong ability to execute hands-on technical work. The AI Lifecycle Team provides the UX backbone and visualization products that Machine Learning Engineers use to shepherd their ideas from data collection to model deployment in the AV. We enable MLEs at Cruise to Run and debug ML pipelines, Initiate data collection, Manage model training, Evaluate model performance, Deploy models to the AV. As a Staff AI ML Engineer, you will collaborate closely with machine learning engineers, research scientists, and other partners to develop state-of-the-art AI solutions that enable the future of intelligent driving technologies across General Motors vehicles.
What You’ll Do:
- Build UX experiences and agentic workflows to improve MLE workflows and productivity
- Build backend integrations to provide unified experience across ML lifecycle
- Raise the bar on system observability, debuggability, and operational excellence, and user experience.
- Own and drive the design and architecture across the ecosystem that meets security and compliance standards
- Establish consistent metrics to measure platform performance & health and create the roadmap for scale, reliability, low latency and speed of development and deployment
- Partner with cross functional teams to understand requirements to design, architect and build framework of UX and backend integrations.
- Partner with engineering teams to ensure seamless end-to-end flow and data quality
- Work across the project lifecycle: requirements, design, prototype, implementation, review, release, monitoring
- Review and approve technical design documents and pull requests.
- Improve and enhance engineering systems documentation and development processes
- Identify and pursue new paths of inquiry, innovation and challenge status quo
- Develop and nurture technical talent within the team and recruiting
Your Skills & Abilities (Required Qualifications)
- Experience building, deploying, and operating high-availability services
- Led large technical initiatives from idea to operationalization and continuous evolution of technical solution to enable new business capabilities and improve efficiencies
- Ability to identify broad challenges (technical, functional, business challenges) worth tackling, and parse them into initiatives within and across engineering teams
- Experience creating ground up enterprise architecture, systems architecture, integration architecture standards, frameworks, and practices
- Programming experience in Python, Java, Go
- Experience working with cloud infrastructure, automations, configuration management, artifact management and building advanced CI/CD solutions
- Experience building production-level frontend applications using React, Angular or similar frameworks
- Strong understanding of JavaScript/TypeScript and dynamic frontend fundamentals
- A passion for all things tech and has a drive to experiment with new technologies to see where they can benefit the business
- BS, MS, or PhD in Computer Science, Math, Physics, or equivalent experience
- Willingness to travel to Sunnyvale, CA as needed
What Will Give You a Competitive Edge (Preferred Qualifications)
- Experience working with technologies including Web services, JSON, GraphQL, agentic workflows
- Experience building interactive tools that are core to people's daily work
- Experience with data science/visualization ML or experimental design knowledge
- Self-motivated, strong execution, impact-delivery oriented
- Excellent communication skills to resolve conflicts, build consensus, communicate risks and provide constructive feedback
Compensation & Benefits
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 $218,800-$335,300. 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.
About General Motors
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.
Key skills/competency
- AI Lifecycle Management
- Machine Learning Pipelines
- Full Stack Development
- System Architecture
- UX/UI Design
- Cloud Infrastructure
- CI/CD
- Backend Integration
- Frontend Development
- Technical Leadership
How to Get Hired at General Motors
- Research General Motors' culture: Study their mission, values (Zero Crashes, Zero Emissions, Zero Congestion), recent news, and employee testimonials on LinkedIn and Glassdoor. Align your application with their vision for intelligent driving technologies.
- Tailor your resume for Staff AI ML Engineer roles: Highlight experience in full-stack development, AI/ML lifecycle management, and building high-availability services. Use keywords like "Python," "React," "cloud infrastructure," "ML pipelines," and "observability" to pass ATS filters.
- Showcase technical leadership and execution: Prepare examples demonstrating your ability to lead large technical initiatives, architect enterprise solutions, and improve engineering systems documentation and processes. Emphasize impact.
- Demonstrate deep technical expertise: Be ready to discuss your proficiency in Python, Java, Go, cloud platforms, CI/CD, and modern frontend frameworks like React or Angular. Practice problem-solving and system design scenarios relevant to AI/ML infrastructure.
- Prepare for behavioral interviews: Articulate your passion for technology, ability to resolve conflicts, build consensus, and drive innovation. Highlight experiences where you've nurtured technical talent and challenged the status quo within a team.
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