Embedded Software Engineer

Embedded Software Engineer – AI/ML at the Edge (Smart Home)

Location: Hybrid – Amsterdam, Netherlands

One of our clients is building a new kind of smart home platform—one that doesn’t just collect data, but acts on it intelligently, locally, and in real time. Think privacy-first, ultra-responsive, and cloud-optional.

We're on the hunt for an Embedded Software Engineer with a passion for AI/ML at the edge to join our founding engineering team. If you’ve deployed models on microcontrollers, wrestled with memory constraints, and enjoy building real-world, voice-, vision-, or behavior-aware products—this is your kind of playground.

What You'll Be Working On:

• Implement TinyML models for edge-based recognition (e.g., sound, gesture, presence, energy usage patterns)
• Use frameworks like TensorFlow Lite for Microcontrollers, Edge Impulse, or TVM
• Develop firmware in C/C++ for MCUs (ARM Cortex-M, ESP32, Nordic, etc.)
• Collaborate on sensor fusion, state detection, and real-time decision logic
• Optimize latency, power, and memory footprint to meet ultra-low-power constraints
• Work closely with product and design teams to bring intuitive, ambient intelligence to life

Must-Have Skills:

• Experience deploying machine learning models on embedded systems
• Proficient in embedded C/C++, low-level driver development, and RTOS or bare-metal environments
• Familiarity with BLE, Wi-Fi, and home automation protocols (MQTT, Matter, Zigbee, Thread)
• Comfortable working with dev tools like logic analyzers, debuggers, and oscilloscopes
• Understanding of model quantization, pruning, and performance tuning for MCUs

Nice to Have:

• Experience with smart home ecosystems (Home Assistant, Apple HomeKit, Google Home, etc.)
• Background in audio processing, presence detection, or environmental monitoring
• Python scripting for automation, tooling, or ML workflows
• Contributions to open-source embedded/IoT or ML-on-the-edge projects