Jobs / United States / General Motors Company
Senior Systems Engineer
General Motors Company · 🇺🇸 5 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 roles8 certified filings for “Software Systems Engineer” (Mechanical Engineers) in CA: $192k–$220k, median $209k. Most were filed at wage level IV (100%) — 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 General Motors is developing hands-off and eyes-off autonomous driving systems intended for broad deployment across consumer vehicles. As part of this effort, GM is investing in sensors and architectures that can be integrated, validated, and operated reliably at scale across diverse vehicle programs and operating environments. We are seeking a Senior Systems Engineer to join the AV team to contribute to defining how autonomous sensing systems are architected and integrated across GM’s autonomy programs. This role focuses on system‑level decisions at the intersection of sensors, embedded software, vehicle platforms, and autonomy software, ensuring that sensing solutions are technically sound, aligned with product intent, and executable in production. In this position, you will perform system‑level trade studies and support the definition of multi-modality sensor suites spanning camera, radar, lidar, and more. You will work closely with AI/ML, platform software, and vehicle integration teams to address real engineering challenges. The role is intended for engineers who are comfortable operating with autonomy, applying first‑principles and physics-based analysis, and delivering robust technical contributions as systems mature from early development into deployed solutions. What You’ll Do You will get the opportunity to contribute to one or more of the following: • Execute system-level trade studies for the design of multi-modality sensor systems supported by detailed modeling of performance and AV behavioral impacts • Develop detailed performance specifications for sensors supported by a strong understanding of sensor physics and signal processing. • Assess performance against product needs to assess risk, quantify impact, and drive continuous improvement • Work closely with cross-functional stakeholders such as simulation, vehicle integration, perception, localization, and validation teams to manage complex interdependencies. • Clearly document technical decisions, trade‑offs, and deliverables. Your Skills & Abilities • Bachelor’s degree in Systems, Electrical, Software, Mechanical Engineering, or a related technical field. Previous work equivalent experience • Experience supporting system architecture, integration, and cross‑domain technical initiatives. • Experience working with sensing systems (camera, radar, lidar, or similar), their usage, and integration. • 5+ years of experience in a sensor intensive field, systems engineering/architecture, autonomy, or other related field. • Experience in requirements development, interface definition, integration, and validation. • Technical depth in signal processing, link analysis, or ML across at least one relevant sensing modality. • Understanding of the challenges of self-driving, and how those map to sensor needs • Demonstrated ability to contribute effectively in complex problem spaces and collaborate across teams. • Experience with Matlab, Python, or other language to support data analysis and analysis tooling development. What Will Give You a Competitive Edge (Preferred Qualifications) • Master’s degree in Engineering or a related technical discipline. • Experience working on L4 (or equivalent) autonomous vehicle programs or advanced remote sensing platforms. • Experience developing, debugging, or integrating embedded or systems‑level software. • Significant experience with automotive autonomy focused lidars and/or radars. • Experience with requirements management tools such as JAMA or DNG. • Experience with system/component validation, including vehicle testing, HIL/SIL, simulation, and large‑scale data analysis Compensation : The compensation information is a good faith estimate only. It is based on what a successful