Jobs / United States / General Motors Company
Software Engineer, AV Data Collection - Early Career
General Motors Company · 🇺🇸 Sunnyvale, California, United States of America
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 roles34 certified filings for “Senior Software Engineer” (Software Developers) in CA: $216k–$265k, median $235k. Most were filed at wage level IV (65%) — 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.
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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 About the Team The AV Logging and Data Recording team within GM’s Autonomous Vehicle Platform Core organization builds the embedded vehicle software that turns real-world driving into high-quality training data for autonomous driving. Our systems collect the sensor, vehicle, and scenario data that AV teams use to improve perception, prediction, planning, and other artificial intelligence capabilities. We focus on capturing the right data from the fleet, preserving privacy, maintaining data quality, and reliably moving vehicle data into the AI development pipeline. We build the software that helps autonomous vehicles learn from the real world. About the Role As a Software Engineer on the AV Data Recording team, you will help build embedded vehicle software that enables fleet-scale data collection for artificial intelligence development. Your work will support how GM autonomous vehicles capture meaningful real-world driving data, validate its quality, enforce privacy requirements, and deliver it for model training, evaluation, debugging, and continuous improvement. You will work on software running on automotive edge platforms and collaborate closely with artificial intelligence, backend, embedded platform, and system development engineering teams to turn real-world driving into high-quality data for autonomous driving development. This is an early-career / new graduate role designed for candidates who have recently completed, or will complete, their Bachelor’s, Master’s, or PhD degree before joining GM. You will be paired with experienced engineers to ramp up on AV software, embedded systems, real-time operating systems, vehicle data pipelines, and the production engineering practices required to support autonomous driving at fleet scale. What You’ll Be Doing • Develop embedded vehicle software that collects high-value data for autonomous driving AI learning. • Build components that capture, filter, validate, package, and offload vehicle and sensor data from the fleet. • Improve data quality, privacy enforcement, reliability, observability, and performance across vehicle data collection workflows. • Build embedded software that controls how high-value driving data is captured, monitored, and delivered from vehicle compute platforms. • Debug complex issues across Linux and QNX-based vehicle software, real-time data recording pipelines, and backend integration points. • Collaborate with AI, backend, embedded platform, and system development engineering teams to ensure collected data meets autonomous driving development needs. • Deliver reliable software through clear requirements, code reviews, automated testing, CI, issue tracking, and incremental development. • Learn and apply production engineering practices for performance testing, regression prevention, rollout readiness, and operational support. Basic Qualifications • Recently completed, or currently pursuing, a Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Artificial Intelligence, Machine Learning, or a related technical field. For completed degrees, graduation must have occurred within the past nine months. • Degree must be completed prior to joining GM. • Strong software fundamentals, including data structures, algorithms, operating systems, computer architecture, or distributed systems concepts. • Solid coding ability in C++, Python, or both, demonstrated through coursework, internships, research, or substantial projects. • Experience developing in a Linux environment through class projects, labs, internships, research, or personal projects. • Ability to debug complex software problems, reason about system behavior, and communicate clearly in a collaborative team environmen