Embedded Software Engineer – AI/ML at the Edge (Energy Optimization)Location: Hybrid – Milan, ItalyOne of our clients is on a mission to change the way buildings and devices use energy—making it smarter, greener, and more autonomous. From predictive heating and lighting to real-time analytics and intelligent load balancing, they’re bringing innovation to the edge.They’re looking for an Embedded Software Engineer who’s excited about working with AI/ML on microcontrollers and low-power edge devices. If you’ve worked with TinyML, sensor-based automation, or embedded control systems, this could be a great opportunity to help shape the future of energy tech.What You'll Do:Build and deploy ML models for real-time energy optimization on embedded hardwareUse frameworks like TensorFlow Lite for Microcontrollers, Edge Impulse, or TVMWrite ultra-efficient embedded firmware in C/C++ for devices like smart meters, HVAC controllers, and energy hubsWork on power-aware scheduling, occupancy prediction, and dynamic control algorithmsIntegrate with energy sensors (current/voltage, temperature, environmental) and communication protocols like Modbus, Zigbee, or LoRaCollaborate with data scientists to compress, quantize, and benchmark models for field deploymentYour Toolkit:Solid experience with embedded programming for ARM Cortex-M or similar MCUsProven deployment of ML models on edge devices (TinyML, TFLM, etc.)Familiarity with sensor interfacing, low-power design, and real-time data processingUnderstanding of energy systems, smart home/building automation, or industrial IoTComfortable with performance tuning, firmware OTA updates, and secure device bootBonus Points For:Experience with building energy management systems (BEMS), home energy storage, or EV chargingBackground in predictive analytics or reinforcement learning for control systemsFamiliarity with Matter, OpenTherm, or Home Assistant integrationsPassion for sustainability, climate tech, and measurable impact