Embedded Software Engineer – AI/ML at the Edge | Hybrid – Berlin, Germany

Are you passionate about pushing intelligence to the very edge of devices? Do you thrive in the intersection of AI/ML, embedded systems, and extreme hardware constraints?

We’re looking for an Embedded Software Engineer with deep experience in Edge AI and TinyML to help us build our client's smart, low-power, real-time solutions for next-generation IoT, wearables, and embedded vision systems.

This is a hybrid role based in Berlin, where innovation in edge computing, machine learning, and embedded tech is booming.

What You'll Do:

• Deploy and optimize ML models on ultra-constrained edge devices
• Work with TensorFlow Lite for Microcontrollers, Edge Impulse, or Apache TVM
• Develop real-time embedded applications in C/C++, integrating sensor data pipelines and ML inference
• Tune performance, latency, and memory footprint for MCUs (ARM Cortex-M, RISC-V, etc.)
• Collaborate with data scientists to convert and quantize models for on-device execution
• Design robust OTA mechanisms, fault handling, and power management strategies

What You Bring:

• Experience deploying TinyML models in production or prototypes
• Proficiency in embedded C/C++, RTOS-based development, and low-level debugging
• Hands-on with MCUs, including memory constraints, power optimization, and peripherals (I2C, SPI, ADC, BLE)
• Familiarity with TensorFlow Lite for Microcontrollers, TVM, or Edge Impulse
• Ability to perform model quantization, pruning, and conversion for low-footprint deployment
• Experience with Python for model training, tooling, and integration scripting

Nice-to-Have:

• Experience with hardware accelerators (e.g., Ethos-U, NPU, DSPs)
• Knowledge of micropower design and battery-operated devices
• Familiarity with OTA updates, secure boot, or embedded Linux environments
• Exposure to real-time sensor fusion, anomaly detection, or embedded vision use cases