At a Glance
- Tasks: Deploy AI algorithms to edge devices and optimise models for real-time applications.
- Company: Innovative company revolutionising the Electrical Distribution Industry with ML technology.
- Benefits: Competitive salary, vibrant office location in Bristol, and opportunities for professional growth.
- Other info: Dynamic team environment with a passion for innovation and collaboration.
- Why this job: Make a real-world impact by preventing outages and enhancing grid health.
- Qualifications: Expertise in C/C++/Rust and Python, with experience in TinyML tools.
The predicted salary is between 60000 - 70000 £ per year.
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 is 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.
- 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.
Senior Embedded Software Engineer employer: Toumetis
At Toumetis, we pride ourselves on being an excellent employer by fostering a collaborative and innovative work culture that empowers our employees to thrive. With a hybrid work model, we offer flexibility alongside opportunities for professional growth in cutting-edge data technologies, ensuring that our team members are equipped to lead the evolution of our data platform. Join us in a dynamic environment where your contributions directly impact our success and the future of data analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Embedded Software Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI algorithms and embedded systems. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your C/C++/Rust skills and understanding model optimisation techniques. Practice coding challenges and be ready to discuss your thought process during problem-solving.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our innovative team.
We think you need these skills to ace Senior Embedded Software Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with C/C++/Rust and any relevant projects you've worked on. We want to see how your skills align with our needs, so don’t be shy about showcasing your expertise!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Tell us why you're passionate about embedded software engineering and how you can contribute to our mission of using ML in the Electrical Distribution Industry. Keep it engaging and personal.
Showcase Relevant Projects:If you've worked on projects involving TinyML tools or model optimization, make sure to mention them! We love seeing real-world applications of your skills, so include links or descriptions of your work.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and we can’t wait to see your application come through!
How to prepare for a job interview at Toumetis
✨Know Your Tech Inside Out
Make sure you brush up on your C/C++/Rust and Python skills. Be ready to discuss how you've used these languages in past projects, especially in relation to model optimisation and firmware integration. The more specific examples you can provide, the better!
✨Understand the Company’s Mission
Familiarise yourself with how the company uses machine learning in the electrical distribution industry. Being able to articulate how your work can contribute to preventing outages or mitigating wildfires will show that you're genuinely interested in their mission.
✨Prepare for Technical Questions
Expect questions about TinyML tools and digital signal processing. Brush up on techniques like 8-bit quantization and weight pruning, as well as your understanding of ARM Cortex-M series or RISC-V architectures. Practice explaining these concepts clearly and concisely.
✨Show Your Collaborative Spirit
Since you'll be working closely with the Data Science team and Embedded Engineers, be prepared to discuss your experience in collaborative environments. Share examples of how you've successfully integrated different technologies or worked on cross-functional teams in the past.
