Overview

This creative team of engineers and scientists are using machine learning tightly integrated with modern electronics to create new classes of devices for the defence and security sectors. As the world goes through a new industrial revolution powered by AI and ML, help lead the UK through it.

You will work across the whole machine learning development lifecycle from initial concepts and architecture decisions through data collection and training to product integration, testing and evaluation. With your models integrated with in‑house leading‑edge electronics, the final products are fully functional prototypes and demonstrator units manufactured at small scale. What’s special about this group is they do this many times per year working across multiple domains. You can be working on computer vision for one project, generative models for the next and then inventing how new methods for another.

With the industry moving so quickly, this company is open to candidates with a variety of backgrounds, from new PhD’s to industry veterans and anything in between.





Requirements

- Strong knowledge of Python and its use in machine learning including hands‑on experience building products with modern ML frameworks such as TensorFlow and PyTorch.
- Broad knowledge of machine learning techniques across multiple domains and the ability to transition into new domains quickly.
- A top degree in a STEM subject. Additionally, a PhD or relevant commercial experience.
- UK nationality for passing security checks.

While not required, experience deploying machine learning onto a range of hardware from resource constrained embedded systems through to cloud computing is desirable. As is any knowledge of GPU programming languages and frameworks (CUDA, ROCm, etc).

Benefits

Benefits include private medical insurance, generous pension scheme and access to local social and sports clubs. Please note, you are required to be onsite full‑time for this role.

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📌 Machine Learning Engineer (27674) (Town of Cambridge)
🏢 Ecm Selection
📍 Town of Cambridge