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Glydways
Posted 20 days agoVerified live 12h ago

Localization Systems Engineer

Brief overview

Remote
MastersOr in progress
3+ yrsMinimum
18 H-1B approvalsDept. of Labor
Requirements Management Tools (Jama)Safety Qualification StandardsLocalization Algorithms and Estimation TheoryKalman FilteringPose Graph OptimizationLIDAR-Based LocalizationComputer Vision-Based LocalizationMapping and CalibrationC++

About the company

Glydways logo
Glydways

Glydways is revolutionizing public transit with carbon-neutral, interconnected transit pathways.

Visa sponsorship history

4 years sponsoring, last filed FY2026

Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.
18H-1B approved
100%approval rate
1new H-1B hires
$210,000median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
20232
20244
20258
20264
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
20231
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Top sponsored roles
Automotive Thermal and HVAC Control EngineerLocalization EngineerSenior Network Design EngineerThermal & HVAC Integration & Validation EngineerSenior Electrical Integration Engineer

Job description

Summary

Glydways is developing an autonomous, carbon-neutral public transit system powered by standardized vehicles on dedicated roadways. The Localization Systems Engineer will support localization, calibration, and mapping software for autonomous ground vehicles by owning requirements, simulation, track, Hardware-in-the-Loop, and unit testing, while collaborating on safety and systems-level solutions.

Responsibilities

  • Be fluent in the localization team's designs at the source-code level, with the ability to understand and reason about C++, engaging directly with the codebase
  • Own the algorithm and test requirements capture process for the localization team, including conducting requirements reviews and revising requirements with autonomy software, systems, and safety teams
  • Write and own simulation and track test scenarios that validate the localization team's systems, including critical safety functions
  • Write and own Hardware-in-the-Loop (HIL) testing for the localization team
  • Champion strong unit test coverage across the localization team's codebase
  • Pursue systems-level solutions in service of the other developers on the localization team, unblocking algorithm and hardware work
  • Work with neighbor teams such as the safety team to fine-tune localization and safety algorithm configuration settings
  • Work closely with teammates by conducting and receiving code reviews and requirements reviews, demonstrating attention to detail and comprehension of complex systems

Skills

  • Experience with requirements management tools (e.g., Jama) and structuring test coverage across unit, simulation, track, and HIL (Hardware-In-the-Loop) levels
  • Familiarity with safety qualification standards related to localization accuracy
  • MSc in Mechanical Engineering, Electrical Engineering, Computer Science, or a related systems engineering field. Does not need to be highly senior, but relevant, demonstrable experience is required
  • Hands-on and flexible/adaptable — willing to get into the details and open to changing approach based on feedback
  • Strong background in localization algorithms/estimation theory including Kalman filtering and/or pose graph optimization
  • Familiarity with LIDAR- and computer-vision-based localization, mapping, and calibration; radar experience a plus
  • Proficiency in C++ sufficient to understand and navigate the team's source code

Qualifications

Must Haves

  • Experience with requirements management tools (e.g., Jama) and structuring test coverage across unit, simulation, track, and HIL (Hardware-In-the-Loop) levels
  • Familiarity with safety qualification standards related to localization accuracy
  • MSc in Mechanical Engineering, Electrical Engineering, Computer Science, or a related systems engineering field. Does not need to be highly senior, but relevant, demonstrable experience is required
  • Hands-on and flexible/adaptable — willing to get into the details and open to changing approach based on feedback

Nice to Haves

  • Strong background in localization algorithms/estimation theory including Kalman filtering and/or pose graph optimization
  • Familiarity with LIDAR- and computer-vision-based localization, mapping, and calibration; radar experience a plus
  • Proficiency in C++ sufficient to understand and navigate the team's source code

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