Graduate Machine Learning Engineer

We're looking for a Graduate Machine Learning Engineer to join our supportive, multidisciplinary team and contribute to the development and application of machine learning solutions for our clients and products. You will help explore, prototype, and implement AI/ML approaches to problems both within and outside our core product offering. Working at the forefront of AI and ML alongside experts in a range of disciplines, you'll help users defend against Defence & National Security threats and directly contribute to safer, more resilient systems in the real world.

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 role provides an excellent opportunity to develop your technical skills, apply academic knowledge in a real‑world commercial environment and gain exposure to client‑facing work.

This role can be office‑based or hybrid, with you expected to work from our Summertown, Oxford office at least one day per week. You will be required to travel to client sites and work at partner locations as needed.

You should be willing and eligible to apply for and obtain UK security clearance if you do not hold an existing clearance.

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• Work closely with colleagues across Science and Engineering, and Product teams to help develop, test and implement ML algorithms that solve complex, real‑world problems efficiently and at scale
  
• Apply established machine learning techniques and libraries to real‑world datasets, with support and mentorship from senior team members
  
• Follow best practices in scientific experimentation, validation, and documentation
  
• Contribute to technical documentation, internal notes, and project reports
  
• Attend client meetings to understand customer needs and how solutions are delivered
  
• Take part in knowledge sharing, training, and professional development activities, including attending relevant events or conferences where appropriate to stay current with emerging ML technologies and techniques and support innovation within the team
  

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• A degree (or expected degree) in Computer Science, Applied Mathematics, Statistics, Physics, or a related STEM field
  
• Familiarity with modern machine learning libraries (e.g. PyTorch or TensorFlow) through coursework, projects, internships or extra‑curricular activity
  
• Experience programming in Python in an academic or project‑based context
  
• An interest in building practical systems that help users understand and benefit from machine learning models
  
• A strong foundation in scientific thinking, with an appreciation for experimental rigour and validation
  
• A willingness to learn, ask questions, and work collaboratively as part of a team
  
• An interest in working alongside our clients to understand and solve their complex problems
  

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• Exposure to working with larger datasets and basic data engineering concepts
  
• Awareness of Agile or iterative development approaches
  
• Experience with additional programming languages (e.g. Java, JavaScript/TypeScript)
  
• The ability to explain technical ideas clearly, with guidance, to both technical and non‑technical audiences
  

We believe in investing in our people by encouraging career and personal development that aligns with your goals and ambitions. We make sure all staff have the tools, time and support they need to shape their own professional development. We want to help you excel at what you do and support your growth within the company.

You’ll enjoy a competitive compensation package and great benefits such as:

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• Hybrid working (some roles may require full time onsite attendance)
  
• Flexible hours
  
• Professional and personal development
  
• 25 days of annual leave (plus Bank Holidays and a company‑wide break over Christmas)
  
• Salary Sacrifice Pension scheme with a 5% employer contribution (minimum 5% employee contribution)
  
• Private Healthcare (including dental and optical cover)
  
• Group Life Cover at three times your annual salary once you pass your probation period
  
• Enhanced Parental and Sickness Leave
  
• Workplace Nursery Scheme
  
• Pet friendly office – A lot of our team bring their dogs to work!
  

While we think the above experience is important, we’re keen to hear from people that believe they have valuable skills, ideas, or perspectives that will make an impact in this role. If our team and mission resonate with you, but you do not necessarily meet all of our requirements, we still encourage you to apply.