Robotics & Embedded Systems Engineer

SPAICE is building geospatial intelligence and autonomous navigation systems for vehicles in GNSS-denied environments. As a Robotics & Embedded Systems Engineer, you will own the hardware, embedded software, and onboard runtime that enables their Spatial AI systems to operate reliably on drones, satellites, and autonomous vehicles in contested environments.

What You’ll Do

• Integrate hardware components including onboard computers, cameras, inertial sensors, radios and flight electronics onto robotic and aerial platforms
• Design and maintain precise time synchronisation across multiple sensors and validate through measurement
• Develop embedded Linux configurations, integrate new sensors from drivers through system configuration, and write low-level software close to hardware
• Develop system services, inter-process communication, logging, health monitoring and automatic recovery for unattended autonomous systems
• Containerise software, build provisioning and update tooling for device fleets, and develop hardware-in-the-loop test benches integrated into CI/CD
• Optimise deep learning models for embedded hardware and port them to new computing platforms and accelerators
• Integrate with flight controllers and autopilots, support field trials, and translate field results into design improvements

What You Need

• M.S. in Computer Science, Computer Engineering, Electrical Engineering, Robotics or a related technical field
• Strong C/C++ and Python skills
• Solid understanding of Linux internals including boot process, system services, drivers and cross-compilation
• Experience with sensor integration and time synchronisation
• Experience with containers, Linux networking and inter-process communication
• Ability to debug across software, hardware, timing and networking using oscilloscopes and logic analysers
• Hands‑on hardware skills including soldering, wiring and reading schematics
• Experience with version control, CI/CD and hardware-in-the-loop testing
• Willingness to travel to test sites

Nice to Have

• Experience deploying and optimising deep learning models on edge hardware
• Experience with microcontroller firmware, real‑time operating systems or drone autopilots
• Linux experience

Competitive compensation, equity options at ground-floor stage, well-being perks including premium gym access, climbing centres and wellness programs

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