ML Hardware Design Engineer

Company: Mignon
Salary: Up to £50k
Location: Newcastle and Hybrid
Role: Full-Time (Fixed Term)

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About Mignon

Mignon Technologies is an innovative startup focused on developing a ground-breaking classification edge-AI coprocessor to accelerate the next generation of energy-efficient AI-enabled devices. Our mission is to revolutionize the integration of AI in intelligent devices, aiming to establish its widespread adoption.

With a team of experts in both hardware and software for AI, and backed by Cambridge Future Tech’s DeepTech Venture Builder, we are committed to making AI ubiquitous.

Job Description:

We are seeking a talented and innovative hardware designer to join our team as part of an Innovate-UK funded project. In this role, you will be responsible for designing and developing the combined power-compute platform for a new Machine Learning (ML) paradigm, capable to be powered not only from a stable power source such as a battery but also an energy harvester.

You will work closely with the founders, ML Embedded Software Design Engineer and ASIC Design Engineer to build the Mignon power-computer platform that customers can use when building their AI systems.

The successful candidate will have a passion for designing Machine Learning hardware and a strong knowledge of the existing hardware design frameworks providing high energy efficiency to Machine Learning.


  • Design and develop power-compute hardware, with energy-harvester power source capability, for improving energy-efficiency of AI-enabled devices using a new Machine Learning paradigm.
  • Work with the core technical team to ensure the hardware interoperates with the accompanying low-level software.
  • Present and demonstrate project results to the founding team.


  • Ability to work independently and make technical decisions autonomously with user requirements in mind (Essential).
  • Strong team player with a willingness to share responsibility and proactively contribute to the project (Essential).
  • Confidence to take ownership of the hardware designs, which will be used by customers to develop Tiny ML platforms for energy-efficient embedded systems (Essential).
  • Experience working with embedded ML frameworks (e.g., Tiny ML, BNNs), low-power and energy-efficient electronics (Essential).
  • Experience in designing computational hardware with power-management elements from scratch (Essential).
  • Experience researching and utilizing cutting-edge ML models and methods (Essential).
  • 3+ years of hardware platform development experience in industry-facing projects (Essential).
  • Experience with hardware-software co-design and power/energy evaluation for embedded systems (Essential)
  • Familiarity with hardware description languages such as SystemC/Verilog/VHDL (Essential).
  • Master’s or PhD Degree from a leading University (Essential).
  • Experience working in a start-up or early-stage Deep Tech projects (Desired).

Please note that the right to work for a UK-registered company is required.

If you are passionate about pushing the boundaries of AI and want to be part of an exciting project, this is an excellent opportunity to contribute to the development of a ground-breaking AI paradigm for edge computing. Join our team and help shape the future of machine learning!


  • Potential to continue into a full-time role after the project is finished.
  • Opportunity to work for an exciting, cutting-edge DeepTech electronics start-up.
  • Pension Scheme.
  • UK public holidays.

Further Details

Ability to commute/relocate:

  • The Role is Hybrid but will require frequent travel to Newcastle upon Tyne, NE1 5JE. Preferably ability to reliably commute or plan to relocate before starting work.


  • Master’s (required)


  • Relevant: 3 years (preferred)

Work authorisation:

  • United Kingdom (required)

Process & Timeline

To apply please send a CV and cover letter to Hiring@Mignon.AI

We review applications on a rolling basis. The interview process will involve a screening call followed by a technical test and interview and then an interview with the project lead and founding team.

Anticipated start date: As soon as possible.  

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