Job description

Who we are: Glydways is reimagining what public transit can be. We believe that mobility is the gateway to opportunity—connecting people to housing, education, employment, commerce, and care. By making transportation more accessible, affordable, and sustainable, we empower communities to thrive and unlock economic and social prosperity. Our mission is to revolutionize transit with a solution that delivers high capacity, exceptional user experiences, unmatched affordability, and minimal environmental impact. The Glydways system is a groundbreaking network of carbon-neutral, interconnected transit pathways powered by standardized autonomous vehicles on dedicated roadways. Operating 24/7 with on-demand access, it offers personalized and efficient mobility—without the burden of heavy upfront infrastructure costs or ongoing taxpayer subsidies. With Glydways, we’re building more than a transportation system; we’re creating a future where everyone, everywhere, has the freedom to move. Meet the team: The Onboard Integration team builds the software foundation that runs on every Glydways vehicle. Part of the Embedded Platform & Integration group, we partner daily with Vehicle Hardware, Autonomy, Safety, and Track Operations to turn a collection of components into a cohesive system on the road. Our work spans streaming data from new sensors, controlling vehicle actuators, building our custom embedded Linux OS, integrating ML runtimes, and writing the tools that keep live track operations moving -we own the glue that makes an autonomous vehicle actually drive. This is software that moves real vehicles carrying real passengers, so reliability isn't a nice-to-have - it's the job. As a Software Engineer on Onboard Integration , you won't be handed narrowly scoped tickets. You'll take a problem from the whiteboard to code running on a vehicle at our test track, get hands-on with the newest hardware in the building, and debug across the software, firmware, and electrical boundaries where the hard problems live. We're looking for engineers who are genuinely excited about autonomous vehicles and PRT, who take initiative in ambiguity, find signals in noisy systems, and own their work end-to-end. What You'll Do: Design, build, and test mission-critical onboard software that runs on every Glydways vehicle, from prototype to deployment on track. Own high-performance interfaces to onboard devices—from cameras, radar, LiDAR, and IMUs to drive-by-wire, controls, and other vehicle systems. Develop and integrate runtimes and middleware so autonomy and ML workloads can execute and communicate reliably onboard. Design and improve systems for live track operations : software deployment, vehicle provisioning, logging, and observability. Collaborate with Autonomy, Hardware, and Operations teams to define interfaces, build evaluation pipelines on real and simulated vehicles, and ship features to the fleet. Investigate and debug issues on the bench and on-vehicle , driving them to root cause and stable fixes. Shape technical direction for the areas you own, and raise the bar through design discussions and code reviews. Knowledge, Skills and Abilities: Required Qualifications: 4+ years of professional software engineering experience, including shipping and supporting production systems. Strong proficiency in C++ or C for production systems—comfortable navigating and improving an existing codebase as well as writing new components. Experience developing device drivers or low-level interfaces for sensors and/or actuators, including use of hardware-in-the-loop (HIL) or similar test frameworks. Experience developing on resource-constrained embedded hardware (CPU, memory, storage, or bandwidth limited). Solid understanding of communication protocols, from low-level (SPI, UART, CAN) to higher-level networking (TCP/UDP). Experience with Linux, especially embedded environments (e.g., Yocto, Buildroot, or similar). Experience with robotics middleware such as ARK, LCM, ROS, or ROS 2. Ability to own features end-to-end: clarifying requirements, designing, implementing, testing, and supporting them in the field. Preferred Qualifications: Familiarity with ML inference runtimes and integrating ML models into production or edge systems (training experience is a plus, not required). Contributions to open-source AI, robotics, or embedded frameworks. Experience with automotive or other real-time, safety-critical systems. Prior work in autonomous vehicles, robotics, or complex mechatronic systems. Experience with performance engineering on embedded CPU/GPU and hardware accelerators. Experience collaborating directly with operations and field teams to debug and improve systems running in production environments. If you're excited about this work but don't check every box, we'd still love to hear from you. We know the best candidates don't always match every line of a job description. *This is a hybrid position, 2-3 days/week onsite in Richmond, CA. No relocation assistance will be provided. The pay range for this position at commencement of employment in California is expected in the range below: $190,000-$220,000 USD plus stock options, commensurate with experience. Glydways provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Requirements

Must-haves

Design, build, and test mission-critical onboard software that runs on every Glydways vehicle, from prototype to deployment on track.
Own high-performance interfaces to onboard devices—from cameras, radar, LiDAR, and IMUs to drive-by-wire, controls, and other vehicle systems.
Develop and integrate runtimes and middleware so autonomy and ML workloads can execute and communicate reliably onboard.
Design and improve systems for live track operations : software deployment, vehicle provisioning, logging, and observability.
Collaborate with Autonomy, Hardware, and Operations teams to define interfaces, build evaluation pipelines on real and simulated vehicles, and ship features to the fleet.
Investigate and debug issues on the bench and on-vehicle , driving them to root cause and stable fixes.
Shape technical direction for the areas you own, and raise the bar through design discussions and code reviews.
Knowledge, Skills and Abilities: Required Qualifications:
4+ years of professional software engineering experience, including shipping and supporting production systems.
Strong proficiency in C++ or C for production systems—comfortable navigating and improving an existing codebase as well as writing new components.
Experience developing device drivers or low-level interfaces for sensors and/or actuators, including use of hardware-in-the-loop (HIL) or similar test frameworks.
Experience developing on resource-constrained embedded hardware (CPU, memory, storage, or bandwidth limited).
Solid understanding of communication protocols, from low-level (SPI, UART, CAN) to higher-level networking (TCP/UDP).
Experience with Linux, especially embedded environments (e.g., Yocto, Buildroot, or similar).
Experience with robotics middleware such as ARK, LCM, ROS, or ROS 2.
Ability to own features end-to-end: clarifying requirements, designing, implementing, testing, and supporting them in the field.

Nice-to-haves

Familiarity with ML inference runtimes and integrating ML models into production or edge systems (training experience is a plus, not required).
Contributions to open-source AI, robotics, or embedded frameworks.
Experience with automotive or other real-time, safety-critical systems.
Prior work in autonomous vehicles, robotics, or complex mechatronic systems.
Experience with performance engineering on embedded CPU/GPU and hardware accelerators.
Experience collaborating directly with operations and field teams to debug and improve systems running in production environments.
If you're excited about this work but don't check every box, we'd still love to hear from you. We know the best candidates don't always match every line of a job description.
This is a hybrid position, 2-3 days/week onsite in Richmond, CA. No relocation assistance will be provided.

Application prep

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mlai

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