Machine Learning Engineer
Mind Foundry
| Company | Mind Foundry |
| Category | Engineering |
| Location | Oxford / Hybrid |
| Remote | Hybrid |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 26 May 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
We’re looking for a Machine Learning Engineer to join a supportive, multidisciplinary team developing AI/ML systems to solve critical Defence and National Security challenges. In this role, you’ll develop robust, production-ready machine learning solutions - taking ideas from early exploration and prototyping through to systems that can operate in complex operational environments. Working alongside specialists across science, engineering, product and delivery, you’ll play a key role in turning advanced ML into trusted capability that supports better decisions where they matter most.
Mind Foundry is at an exciting stage of growth, with increasing demand for AI-enabled capability across our markets. We specialise in helping customers make sense of the ever-increasing volumes of data collected by sensors, platforms and systems at the speed of relevance. We often find ourselves working at the edge in complex environments where power, compute, and bandwidth are in short supply. As a Machine Learning Engineer, you’ll work on problems that are technically challenging, operationally important and genuinely meaningful. You will help turn advanced AI and ML approaches into deployable capability that can support better, faster decision-making in demanding real-world environments. What makes the work distinctive is the combination of technical depth, practical engineering and responsible delivery. 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 be required to travel to and work from client sites and partner locations. When not working onsite, this role can be office-based or hybrid from our Summertown, Oxford office.
You will need to hold existing or be eligible for UK Security Vetting (SC), details of which can be found on the Gov UK website .
Key day-to-day activities:
Design, build and iterate ML prototypes and production-ready capability for complex, real-world Defence and National Security use cases.
Translate research outputs, experimental approaches and customer problems into maintainable, testable and deployable ML systems.
Work with real-world data sources, including noisy, incomplete, high-volume or streaming data, to develop approaches that are robust and operationally useful.
Collaborate closely with Machine Learning Scientists, Software Engineers, Product Managers and customer-facing teams to shape solutions that are technically credible and user-relevant.
Write clean, maintainable and well-tested code, contributing to engineering standards, reproducibility and long-term ownership.
Support evaluation, validation and assurance of ML models, including communicating model behaviour, limitations and trade-offs to technical and non-technical stakeholders.
Contribute to deployment approaches for constrained or complex environments, including edge settings where compute, power and bandwidth may be limited.
Provide technical input into bids, demonstrations, customer discussions and partner engagements where required.
Keep up to date with emerging ML methods, tools and implementation approaches, and share relevant knowledge with the wider team.
Core Skills & Experience:
A degree in Computer Science, Applied Mathematics, Statistics, Physics, or a related STEM field (or equivalent practical experience).
Strong programming skills in Python, with experience producing clean, reproducible, well-tested and well-documented code.
Hands-on experience with production infrastructure, which may include Docker, Linux, CI/CD, MLOps, cloud platforms, and model serving architectures.
Familiarity with modern ML libraries and tooling, with the ability to select pragmatic approaches for real-world problems.
Comf
You found the opening. Now track it.Tracker, radar and AI drafts in one place.erioun.com →