About Us
We are an AI-native, VC-backed startup building a multimodal Foundation Model with a profound understanding of retail, designed to hyper-personalise every shopper touchpoint. To realise our vision, smaller downstream models must run on the edge on-device.
As an Edge AI Engineer, you will bridge research and production, ensuring our models are optimised for on-device inference. If you want to operate at the frontier of deep learning and real-world deployment, this role is for you.
What You Will Do
* Deploy smaller task-specific models built on top of our offline Foundation Model to run on-device during live shopping experiences.
* Build robust evaluation pipelines that ensure on-device implementations mirror the performance of offline systems.
* Integrate models with mobile inference backends such as TensorFlow Lite, ONNX Runtime Mobile, MediaPipe or custom native models.
* Build and manage real-time on-device data stores for low-latency context and lookup.
* Collaborate with Research Scientists and Research Engineers to ensure model design is edge-aware and device-compatible from the start.
* Test and validate performance in live, resource-constrained environments.
What We Look For
* 2 to 4 years of experience deploying deep learning models to mobile or edge devices, ideally Android.
* Strong proficiency in Python and Java or Kotlin, with experience translating ML code between languages.
* Practical experience with mobile inference frameworks such as TensorFlow Lite, ONNX Runtime, or similar tools.
* Familiarity with GPU acceleration on mobile (e.g., GPU delegates, Vulkan) or ARM-based systems is a plus.
* A mindset that combines engineering rigour with startup adaptability: you are comfortable solving hard technical challenges quickly and creatively.
Nice to Have
* Working knowledge of Python and/or model training frameworks like Pytorch or similar
* Working knowledge of JNI on Android and/or C/C++
Why Join Us
* You’ll be part of a small, high-output team where intensity and focus are the norm.
* You’ll take ideas from research to live deployment fast and see your work shape real shopper experiences.
* You’ll own problems end-to-end, from messy prototypes to stable, production-grade systems.
* You’ll work alongside people who care deeply, move quickly, and hold a high bar for excellence.