Jobs / United States / General Motors Company
Senior ML Infrastructure Engineer - Embodied AI Scaling Foundations
General Motors Company · 🇺🇸 3 Locations
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What General Motors Company paid sponsored hires in similar roles2 certified filings for “Senior ML Engineer - Embodied AI Offboard Percepti” (Data Scientists) in CA: $230k–$240k, median $235k. Most were filed at wage level III (100%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — General Motors Company
The US Department of Labor certified 606 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 267 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for General Motors Company →
About the role
Job Description At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. Are you passionate about accelerating the future of autonomous driving? Join the Embodied AI Infra Foundation team at General Motors, where we build the critical infrastructure that powers every machine learning engineer working on our cutting-edge Autonomous Driving models. From foundational models to state-of-the-art optimization, our work is at the heart of our mission. About the team: Our goal is simple: dramatically accelerate the machine learning development cycle, freeing our engineers to focus entirely on enhancing the safety and performance of the car, rather than managing infrastructure. We are committed to delivering products that are performant, easy to use, and exceptionally reliable. Your success will be measured by the success of our partner teams who rely on our robust systems to build the world's most advanced driverless vehicles. As a Senior ML Infra Engineer, you will build critical infrastructure that powers every machine learning engineer working on our cutting-edge Autonomous Driving models. From foundational models to state-of-the-art optimization, our goal is simple: dramatically accelerate the machine learning development cycle. We are committed to delivering products that are performant, easy to use, and exceptionally reliable. Your success will be measured by the success of our partner teams who rely on our robust systems to build the world's most advanced driverless vehicles. What you'll do: • Lead the design, implementation, and deployment of scalable platforms and tools that drive machine learning model training and evaluation workflows across GM. • Own complex technical projects end-to-end, making key architectural decisions and technical trade-offs. You will be a core contributor to team planning, design reviews, and code quality. • Take a holistic view of projects, considering their impact across multiple teams, and proactively drive technical prioritization. Collaborate closely with partner teams to ensure maximum benefit from the systems we build. • Help shape our team through technical interviewing with high, well-calibrated standards, and play an essential role in recruiting. Mentor and onboard junior engineers and interns, helping them grow their careers. Your Skills & Abilities (Required Qualifications) • 3+ years of experience building large-scale distributed systems/applications or advanced ML Applications. • Proven track record of building robust frameworks with high-quality, long-lasting APIs. • Deep understanding and practical experience with machine learning algorithms. • Expertise in building reliable, highly performant, and cost-efficient systems leveraging modern cloud infrastructure. • Hands-on experience with the entire ML development lifecycle and MLOps practices. • Demonstrated ability to collaborate effectively across multiple teams and organizations. • Proficiency working with containerization and orchestration technologies (Docker, Kubernetes). • A strong passion for self-driving technology and its transformative potential. • Exceptional coding skills in Python or C++. • BS, MS, or PhD in Computer Science, Math, or equivalent practical experience. Exceptional candidates may also have: