Edge AI & Embedded Systems Engineer

About the RoleWe're building AI-powered solutions that run directly on physical hardware and edge devices wearable devices and vehicle-based systems among them. This is a hands-on engineering role for someone who's comfortable at the intersection of hardware and software, getting AI inference running reliably under real-world constraints of power, memory, latency, and environmental conditions.You'll lead the technical development of our first wearable AI device deployment, then extend that capability to sensor-based systems in vehicle and industrial contexts as the program grows.What You'll Do•     Lead end-to-end technical development of an AI enabled wearable device solution, from hardware integration through to field deployment•     Manage hardware-software integration, including device SDKs, drivers, firmware interfaces, and sensor APIs•     Design and implement AI inference pipelines optimised for edge compute constraints power, memory, and latency•     Evaluate, select, and implement edge AI frameworks such as ONNX, TFLite, TensorRT, or similar•     Develop and execute hardware-in-the-loop testing and validation protocols•     Extend the platform's edge AI capability to vehicle and sensor-based systems, including integration with onboard diagnostics and telematics data•     Document hardware integration processes, deployment playbooks, and maintenance procedures•     Stay current with developments in edge AI hardware, wearable computing, and embedded AI frameworksWhat We're Looking ForRequired:•     Degree in Computer Engineering, Electrical Engineering, Computer Science, or a related discipline•     1–3 years' experience in embedded systems, edge AI or hardware-software integration•     Hands-on experience with embedded or edge devices wearables, IoT hardware, industrial devices, or similar•     Proficient with hardware communication protocols: I2C, SPI, UART, BLE, and device SDK integration•     Demonstrated experience deploying ML/AI models on resource-constrained or edge hardware•     Able to debug at the hardware-software boundary using appropriate embedded debugging tools•     Proficient in C/C++ for embedded systems, and Python for AI/ML pipeline developmentPreferred:•     Experience with vehicle sensor systems or automotive telematics CAN bus, OBD-II, or similar in vehicle data protocols•     Experience with computer vision pipelines object detection, image classification, or scene understanding•     Familiarity with AR or wearable hardware platforms•     Exposure to Io platforms and sensor network architectures•     Experience with modern AI-assisted development tooling•     Prior work in field deployment of edge AI solutions in an industrial or logistics environmentWhat We Offer•     The opportunity to own and shape a strategic, growing capability from the ground up•     Direct collaboration with senior technical leadership on solution architecture and deployment strategy•     A hands-on role spanning both cutting-edge software and real physical hardware deployment