Toumetis
Senior Embedded Software Engineer

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Toumetis Job Description
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.
We have a friendly working environment with flexible hours, WFH (1-2 days in the office P/W), regular social events, Private Medical/Optician/Dental insurance, a very competitive pension scheme and you will be supplied with a MacBook Pro.
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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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.


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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 - george.wrightson@Toumetis.com.
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
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