Jobs / United States / General Motors Company
Systems Engineering Manager - Autonomy Behavior
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 roles1 certified filing for “Manager - Systems Engineering” (Information Technology Project Managers) in TX: $202k–$202k, median $202k. 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 Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to Sunnyvale, CA three times per week at minimum or other frequency dictated by the business. The Role As a Manager of Autonomy Behavior Systems Engineering, you will lead a team responsible for how autonomous vehicle behavior is specified, evaluated, and supported by evidence. You will set technical direction while creating the conditions for engineers to do their best work across behavior, software, simulation, safety, legal, product, and operations. You will bring deep experience evaluating autonomous vehicles in commercial fleets and understand the difference between a test that produces a result and a validation system people can trust. You will help define the systems engineering approach, connect requirements to simulation and release evidence, and ensure the team delivers methods and products that support developers, release decisions, and launch decisions. What You’ll Do • Lead and develop a team of autonomy behavior systems engineers, setting expectations for technical quality, execution, communication, and growth. • Set the systems engineering and validation direction for major capabilities and cross-cutting behaviors, connecting requirements, coverage, simulation validity, metrics, acceptance criteria, and release evidence. • Guide the development of scalable behavior evaluation and simulation systems across synthetic tests, road data, and counterfactual references, including scenario sourcing, orchestration, data quality, and reproducibility. • Partner across Engineering, Safety, Legal, Product, and Operations to resolve ambiguity, build alignment, and communicate clear recommendations for engineering, release, and launch decisions. Your Skills & Abilities (Required Qualifications) • Master’s degree in systems engineering, mechanical engineering, aerospace engineering, electrical engineering, computer science, robotics, or a related field. • 8 or more years of professional experience in systems engineering, autonomous vehicles, robotics, vehicle development, simulation, or safety-critical validation. • A proven record of evaluating autonomous vehicles for a commercial fleet, launch, supervised release, or other high-consequence product decision. • Deep systems engineering fundamentals, including architecture and decomposition, use-case and scene modeling, requirements strategy, interface definition, verification and validation planning, and traceability. • Professional experience defining or leading simulation evaluation at scale, including the trade-offs between coverage, confidence, runtime, cost, and simulation validity. • Strong Python experience. You should be comfortable reviewing production-quality analysis or validation software and understanding how tools and data pipelines support engineering decisions. • Strong communication skills and the ability to create alignment among teams with different goals, terminology, and technical perspectives. • Demonstrated stakeholder management and technical leadership across organizational boundaries. You have led work through influence, not only through formal authority. • Experience as a Tech Lead, Technical Lead Manager, or people manager responsible for delivering complex technical work through a team. • A track record of developing engineers, giving clear feedback, supporting career growth, and building an inclusive, accountable team culture. What Will Give You a Competitive Edge (Preferred Qualifications) • Human benchmarking for behavior and safety evaluation, including attentive human benchmark construction, human percentile methods, expert review, and the limits of human references. • Experience with hazard analysis,