Skills this job asks for
StatisticsLeadershipPythonC++Machine learning
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Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 290 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.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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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.
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✓
What Waymo LLC paid sponsored hires in similar roles9 certified filings for “Systems Engineer” (Mechanical Engineers) in CA: $187k–$235k, median $230k.
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Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 290 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. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-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 Waymo LLC paid sponsored hires in similar roles
- 9 certified filings for “Systems Engineer” (Mechanical Engineers) in CA: $187k–$235k, median $230k. Most were filed at wage level IV (63%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
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.
About the role
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
Waymo's Systems Engineering team works together to blend software and hardware systems in groundbreaking new ways. We set the high performance standards that ensure our vehicles run smoothly and keep passengers safe, then design and perform the tests that validate that performance. We're looking for talented teammates who’ll help us maintain strong teamwork and are passionate about driving results.
You will:
• Define the approach for quantitative safety risk analysis across sensing and perception systems engineering, building on top of Waymo-wide risk assessment and management methodologies. You will design, develop, and implement sophisticated quantitative methods and statistical models for evaluating end-to-end performance for current and counterfactual sensor suites.
• Apply the defined approach for selected events that occur rarely or have scarce operational data. The generalized goal is to assess behavioral safety risk across a wide variety of situations like interacting with pedestrian crowds, navigating around floods, and degraded sensing in construction zones.
• Develop and prototype novel workflows to:
• Analyze to determine the required performance levels of various sensing and perception tasks
• Support trade studies to inform architectural decisions for perception hardware or software
• Estimate exposure of events relevant to perception-driven behavioral risk
• Improve quantitative rigor, standardization, efficiency of execution, and reporting of end-to-end risk from V&V test outcomes in complex contexts.
• Expand existing methodologies that are crucial for breaking into new operational design domains and addressing emergent challenges
• Collaborate closely with:
• Onboard Software and Evaluation for mapping perception evaluation and planner evaluation to end-to-end risk in large models
• Test Engineering for cross-calibrating risk from V&V results across various methodologies and coverage competencies, and providing actionable data to improve Waymo’s test tooling across public roads/closed course tests and simulations on logged/synthetic scenarios
• Systems Safety for appropriate allocation of quantitative risk across functional insufficiencies
• Clearly communicate complex quantitative findings and recommendations to diverse stakeholders, including senior leadership, to enable safety at scale. You will collaborate deeply within SysEng and cross-functionally with Product, Simulation, and Data science teams to advance safely and deliver excellence.
You have:
• Bachelors or higher degree in computer science, math, physics, engineering, or a related field
• 10+ years of engineering experience with demonstrated delivery of high-stakes technical roadmaps that successfully resolved architectural friction and deployed business-critical systems
• Experience using AI productivity tools for analysis and workflow development
• Proficiency and experience in:
• Vehicular robotics (development or evaluation)
• Software development (Python or C++)
• Statistical or predictive modeling
• Experimental design and developing m
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