Embedded Machine Learning Engineer

An embedded machine learning engineer in Edinburgh will develop and deploy models to process sensor data from real-world environments under strict resource constraints. The role involves transforming noisy, uncontrolled sensor streams into reliable, real-time classification models suitable for embedded devices with limited memory and power. Candidates must optimise models for embedded deployment, integrating them into hardware platforms and collaborating with firmware engineers. Requirements include experience with sensor data, Python, TensorFlow Lite, and edge deployment tools, along with strong problem-solving skills for field validation and iteration. The engineer will work from sensor data collection to model optimisation, accuracy validation, and platform expansion, contributing to cutting-edge applications in real-time detection systems.