Embedded Software Engineer

Embedded Software Engineer – AI/ML at the Edge (Grid-Edge Control)

Location: Onsite – Vienna, Austria

Company: GridTech Startup | Real-Time Energy Control Systems | EU-Funded + Industry Partnerships

The power grid is changing fast—distributed, digital, and decentralized. At our client's startup in Vienna, they’re building edge intelligence that enables real-time energy control at the grid’s edge: smart inverters, microgrid controllers, and predictive load managers.

We’re looking for an Embedded Software Engineer with experience in AI/ML at the edge, capable of bringing autonomy to critical grid devices. You’ll work at the crossroads of embedded systems, real-time control, and sustainable energy innovation.

What You'll Be Working On:

• Develop and deploy ML models on embedded controllers for grid-edge devices (smart inverters, load balancers, DERs)
• Use frameworks like TVM, TensorFlow Lite for Microcontrollers, or Edge Impulse
• Build real-time firmware in C/C++ for ARM Cortex-M/R cores, optimized for deterministic control
• Interface with power electronics and grid protocols (e.g., Modbus, IEC 61850, MQTT)
• Work on predictive control, fault detection, and local decision-making logic
• Collaborate with grid experts to implement safety, resilience, and islanding logic in edge nodes

Required Experience:

• Strong background in embedded systems programming (C/C++, RTOS, bare-metal)
• Experience deploying AI/ML models to microcontrollers
• Knowledge of power systems, control theory, or real-time automation
• Familiarity with digital signal processing, sensor data fusion, and embedded diagnostics
• Comfort with hardware testing, instrumentation, and field validation

Bonus Points:

• Work with DERs, BESS, inverters, or microgrid controllers
• Experience with real-time monitoring, firmware OTA updates, or edge cybersecurity
• Background in predictive maintenance, demand response, or energy forecasting
• Passion for clean energy and smart infrastructure