Machine Learning Engineer - National Security (London)

We’re looking for a Machine Learning Engineer to join a supportive, multidisciplinary team developing AI/ML systems to solve critical National Security challenges. As a Machine Learning Engineer, you’ll develop robust, production-ready machine learning solutions, exploring, prototyping, and deploying ML approaches from initial concept through to live operation. Working at the forefront of applied AI alongside experts across multiple disciplines, you’ll help users defend against Defence and National Security threats, directly contributing to safer, more resilient systems deployed where they matter most. 

Mind Foundry works on some of the most complex and urgent challenges in Defence and National Security. We specialise in supporting customers across the community to make sense at the speed of relevance from the ever-increasing volumes of data collected by sensors and systems. We often find ourselves working at the edge in complex environments where power, compute, and bandwidth are in short supply. The work is challenging, the customer needs products and applications they can trust, and the sense of achievement is therefore substantial.  

This is an opportunity to innovate at the forefront of applied machine learning, tackle high-impact real-world problems, grow your technical skills, and shape the way AI/ML solutions are delivered to critical operational environments. 

Because of the nature of this work: 

• You will need to hold existing or be eligible for UK Developed Vetting (DV), details of which can be found on the Gov UK website.  

• Be expected to work primarily onsite at our clients’ sites in London. Please consider your commute when applying.  

 

Key day-to-day activities: 

• Design and build prototypes and robust, production-ready ML solutions. 

• Work collaboratively with colleagues across the Mind Foundry team (Product Managers, Machine Learning Scientists, Software Engineers) to solve critical National Security challenges. 

• Maintain and develop a good working knowledge of state-of-the-art ML methods, software tools and implementation methods. 

• Write maintainable production code and promote best practices for code quality in a scientific codebase. 

• Provide advice and explain core ML concepts to our customers and partners. 

 

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