Software Engineer (Onboard Integration)

Glydways; Richmond (VA); On-site; USD 120,000 - 170,000; Full time

Job summary

Glydways is seeking a Software Engineer for the Onboard Integration team. You will build the software foundation for Glydways vehicles, spanning sensors, actuators, and embedded Linux to run ML workloads and live track operations.

You will own features end-to-end, working across software, firmware and electrical boundaries, collaborating with Hardware, Autonomy and Operations teams to ship reliable, real-time onboard systems.

Qualifications

• 4+ years of professional software engineering experience, shipping and supporting production systems.

Responsibilities

• Design, build and test mission-critical onboard software for Glydways vehicles.
• Own high-performance interfaces to onboard devices (cameras, radar, LiDAR, IMUs).
• Develop runtimes and middleware for ML workloads on embedded platforms.
• Collaborate with Autonomy, Hardware and Operations teams to define interfaces and deploy features.
• Debug across software, firmware and electrical boundaries to root cause issues.

Skills

C++

C

Tools

Yocto

Buildroot

ROS 2

HIL

Job description

• 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
• 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

Solid understanding of communication protocols, from low-level (SPI, UART, CAN) to higher-level networking (TCP/UDP)Ability to own features end-to-end: clarifying requirements, designing, implementing, testing, and supporting them in the field4+ years of professional software engineering experience, including shipping and supporting production systemsStrong proficiency in C++ or C for production systems—comfortable navigating and improving an existing codebase as well as writing new componentsExperience with Linux, especially embedded environments (e.g., Yocto, Buildroot, or similar)Experience developing device drivers or low-level interfaces for sensors and/or actuators, including use of hardware-in-the-loop (HIL) or similar test frameworksExperience developing on resource-constrained embedded hardware (CPU, memory, storage, or bandwidth limited)Experience with robotics middleware such as ARK, LCM, ROS, or ROS 2Familiarity 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 frameworksExperience with automotive or other real-time, safety-critical systemsPrior work in autonomous vehicles, robotics, or complex mechatronic systemsExperience collaborating directly with operations and field teams to debug and improve systems running in production environments