Senior Embedded Software Engineer

Senior Embedded Software Engineer

Salary £60,000 - £70,000+ DOE

About our Company

As a company we specialise in using ML within the Electrical Distribution Industry to predict outages and equipment failure. The work has huge real world implications, helping prevent anything from large scale outages to mitigating wildfires.

Our engineers, developers and data scientists share a passion for innovation and are dedicated to providing our customers with solutions that enable new insights that revolutionise business processes.

Our main office

Based in the heart of the wonderful and vibrant city of Bristol around the corner from the SS Great Britain and one of the street artist, Banksy’s infamous works. It is only a short stroll to Cargo and the Harbourside area which boasts a tremendous array of bars, restaurants, cafes and other assorted nice places all ripe for a lunch break visit or relaxing after work.

What will you be working on?

Working alongside our Data Science team you will be responsible for deploying AI algorithms to edge devices like Smart Meters, acting as a bridge between high level data science and low level hardware engineering.

You will be responsible for taking trained models and "shrinking" them to fit within the kilobyte-range memory and milliwatt power budgets of our hardware. Your work will enable real-time anomaly detection, load forecasting, and grid health monitoring directly at the point of consumption.

Key Responsibilities

• Model Optimization: Convert high-level Python/TensorFlow/PyTorch models into optimized C++, Rust or Flatbuffer formats using TensorFlow Lite for Microcontrollers or Edge Impulse.
• Resource Management: Implement techniques like 8-bit quantization, weight pruning, and knowledge distillation to ensure models run within <256KB of RAM and minimal Flash storage.
• Firmware Integration: Collaborate with Embedded Engineers to integrate inference engines into the device's firmware (RTOS-based) without disrupting primary metrology functions.
• Signal Pre-processing: Develop efficient Digital Signal Processing (DSP) pipelines to clean raw voltage/current data before it reaches the AI model.

Required Technical Skills

• Languages: Expert proficiency in C/C++/Rust (for the device) and Python (for the model pipeline).
• Frameworks: Deep experience with TinyML tools (TFLite Micro, CMSIS-NN, or STM32Cube.AI).
• Hardware Knowledge: Familiarity with ARM Cortex-M series or RISC-V architectures.
• Mathematical Foundation: Strong understanding of linear algebra and signal processing (FFTs, digital filters).

Interested in the role?

For a confidential discussion about this role, or if you feel your skillset would be of benefit to the Toumetis team but doesn’t match a specific job spec, please get in touch with our Talent Acquisition team - .