Localization Systems Engineer

🕒 September 14

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

⚙️ Systems Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 10%

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Glydways

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2016

🚗 Transport

🤖 Artificial Intelligence

👥 B2C

Transport • Artificial Intelligence • B2C

Glydways is a company focused on transforming public transit through innovative and efficient mobility solutions. Their unique approach includes a seamless self-driving fleet operating on dedicated guideways, allowing for direct and congestion-free rides. Glydways aims to make transit accessible and financially sustainable, promoting the idea that access to mobility is essential for opportunity and community engagement.

📋 Description

• Develop software for localization, calibration, and mapping of autonomous robotic ground vehicles. • Write and maintain C++ onboard software. • Conduct data analysis, often using Python, in a common software repository. • Own algorithm and test requirements capture, including requirements reviews and revisions with autonomy software, systems, and safety teams. • Write and own simulation and track test scenarios validating localization systems, including critical safety functions. • Write and own Hardware-in-the-Loop (HIL) testing. • Champion strong unit test coverage across the localization codebase. • Pursue systems-level solutions that unblock algorithm and hardware work. • Collaborate with safety and neighboring teams to fine-tune localization and safety algorithm configuration settings. • Conduct and receive code reviews and requirements reviews.

🎯 Requirements

• 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. • 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 is a plus. • Proficiency in C++ sufficient to understand and navigate the team's source code.