Jobs / United States / General Motors Company
Staff Software Engineer - Machine Learning
General Motors Company · 🇺🇸 Remote - United States · Remote
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 roles3 certified filings for “Senior Machine Learning Engineer” (Software Developers) in WA: $150k–$230k, median $225k. Most were filed at wage level IV (67%) — 4 lottery entries, ≈61% 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.
Or apply yourself on the official page →
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 Role: The Smart Agents group is responsible for building the ML models and system to simulate road users in a variety of situations and generate the scenarios used for testing and training AV driving policies. If you think of Simulation as a video game our autonom ous vehicles train on to learn to drive, the Smart Agents team develops the ML/AI models that cont rol the other characters in the video game to interact in realistic ways as the av dr ives- eg , the other vehicles, bikers, and pedestrians. Our technology stack includes Generative AI models (GPT) and Reinforcement Learning (RL) policies . The Smart Agents group work closely with the rest of the Simulation, and our partners Behaviors, Perception, and Safety Engineers. The specific duties may include ML/RL model development as well as training loop development, streamlining optimization, integration, creating ML infrastructure , metrics, and data pipeline s for production model de plo yment as well as f or fast experimentation cycles. What You'll Do: • Support the team in developing machine learning (ML) and reinforcement learning (RL) models, including training loop development and optimization. • Streamline integration and create ML infrastructure, metrics, and data pipelines for production model deployment and rapid experimentation. • Work as part of an ML team and cont ri bute strong software engineering (SWE) expertise . • Support the ML team in accelerating project timelines, particularly in areas related to Autopilot, Lane Keep, and autonomous vehicle (AV) technologies. • Experience in simulation and robotics is highly desirable, with a preference for candidates from AV or robotics backgrounds rather than solely cloud-focused companies. Your Skills & Abilities: • 4+ years of experience in the field of robotics or latency-sensitive backend services • Background working with machine learning teams, algorithms, and models • Bonus: Experience building highly performant ML and system pipelines • Strong programming skills in modern C++ or Python Bonus: • Experience with profiling CPU and/or GPU software, process scheduling, and prioritization • Passionate about self-driving car technology and its impact on the world • Expertise in setting architectures that are scalable, efficient, fault-tolerant, and are easily extensible allowing for changes overtime without major disruptions. • Ability to design across multiple systems. Ability to both investigate in sophisticated areas as well as a good breadth of understanding of systems outside of your domain. • Ability to wear several hats shifting between coding, design, technical strategy, and mentorship combined with excellent judgment on when to switch cont exts to meet the greatest need. • Track record in deploying perception/prediction/av models into real world environments Your Skills & Abilities : • 4+ years of experience in the field of robotics or latency-sensitive backend services • Proven experience in machine learning and classification. Familiar with ML frameworks such as Tensorflow or PyTorch • Experience building highly performant ML and system pipelines • Strong programming skills in modern C++ or Python • Experience with profiling CPU and/or GPU software, process scheduling, and prioritization • Passionate about self-driving car technology and its impact on the world • Expertise in setting architectures that are scalable, efficient, fault-tolerant, and are easily extensible allowing for changes overtime without major disruptions. • Ability to design across multiple systems. Ability to both investigate in sophisticated areas as well as a good breadth of understanding of systems outside of your domain. • A