We are looking for enthusiastic people to join our team and contribute to our goal of creating disruptive machine intelligence technology!

You will join the company at the most exciting time when we are scaling up and getting traction with customers so you will be able to see your hard work deployed in the real word.

We are based in central Manchester and offer competitive salaries and a share option scheme for eligible employees.

If you have any questions or if you would like to apply please email




As a Machine Learning Engineer, you will be responsible for the design, development, training and testing of neural networks that are capable of classification and segmentation using one- to few- reference examples. You will be part of the Engineering team and you will work closely with the product owner and technical lead on assessing the feasibility and business viability of products in the smart devices and inspection industries, based on customer requirements. At the start of development, you will identify appropriate training data sets, suggest and implement improvements to the existing neural network models, streamline coding, training, validation and testing such that all customer needs are satisfied.


  • 3+ years of experience in building machine learning applications for computer vision
  • MSc or PhD Degree in Computer Science, Engineering, Mathematics or Statistics
  • Strong software skills in building complex and well-designed cloud-based AI models
  • Excellent programming skills in Python
  • Good knowledge of machine learning frameworks, such as TensorFlow or PyTorch
  • Good mathematical skills especially in probability and statistics
  • Experience with software development version control and engineering principles
  • Ability to work independently
  • Effective communicator of complex data and methods to experts and non-experts


  • Understanding of metric- and model-based meta learning techniques
  • Experience in developing and training neural networks that use generative models such as Variational Autoencoders and Generative Adversarial Networks
  • Good knowledge of the techniques behind transfer learning
  • Proficiency in studying performance of models with ablation studies
  • Optimization of models for deployment to devices with limited compute and memory



As an Application Engineer, you will be responsible for designing and implementing user interfaces and APIs for edge-based machine learning applications. You will be working in our Platforms team and the UIs/APIs that you develop will be used by machine learning and software engineers to deploy neural network models in an optimal way to edge devices such as embedded and mobile.


  • 3+ years working on user interface and API/SDK design
  • Familiarity with the underlying hardware of edge/mobile devices
  • Solid programming experience in (eg) Java/C++/Python
  • Familiarity with version-control tools such as Git
  • Understanding of machine learning concepts
  • Knowledge of ML frameworks such as TensorFlow/PyTorch
  • Ability to develop with ML frameworks under Android NN SDK or iOS CoreML.
  • Experience developing product-ready user interfaces
  • Deployment of applications to Android/iOS
  • Ideally, you will have familiarity with fast incremental learning on edge devices

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