At a Glance
- Tasks: Lead software deployments and create robust machine learning solutions for real-world applications.
- Company: Join Mind Foundry, a leader in applied AI for Defence and National Security.
- Benefits: Enjoy hybrid working, flexible hours, and a competitive compensation package.
- Other info: Dynamic team environment with opportunities for personal and professional growth.
- Why this job: Make a real impact by tackling high-stakes challenges with cutting-edge technology.
- Qualifications: Degree in STEM or equivalent experience; strong programming skills in Python required.
We’re looking for a Machine Learning Engineer (Forward Deployed) to join a supportive, multidisciplinary team delivering real-world AI/ML systems into operational environments. In this role, you’ll lead software deployments, working closely with users and stakeholders to translate their problems into robust, production-ready machine learning solutions. You’ll rapidly explore, prototype, and deploy ML approaches both within and beyond our core product offerings, taking ownership 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. 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.
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. You should be willing and eligible to apply for and obtain UK security clearance if you do not hold an existing clearance.
Responsibilities include:
- Moving models from research/prototype to live, high-impact production environments, adapting those solutions to client-specific data, systems, and interfaces.
- Extending and improving internal ML platforms, tooling, and best practices, incorporating learnings from deployments back into shared frameworks.
Qualifications:
- A Degree in Computer Science, Applied Mathematics, Statistics, Physics, or a related STEM field (or equivalent practical experience).
- Strong engineer with demonstrated proficiency in programming languages such as Python, producing clean, reproducible, well-tested, and well-documented code suitable for long-term ownership and handover.
- Hands-on experience with production infrastructure, including Docker, Linux, CI/CD, MLOps, cloud platforms, and model serving architectures.
- Prior experience working with government customers, defence contractors, or in military environments.
- Experience in areas of model development, data processing and streaming (Spark, Kafka), microservices in python (Flask or FastAPI), and interactive visualisations and User Interfaces (Streamlit, Plotly, Gradio etc).
- Broader software engineering experience (e.g. Java, Node.js, React, PostgreSQL, system architecture, DevOps).
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:
- Hybrid working
- 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 (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
- Dog-friendly office!
For more information, please visit our website or email recruitment@mindfoundry.ai.
In person meet the team at our Summertown office.
Machine Learning Engineer (m/w/d) in Oxford employer: Mind Foundry
Mind Foundry is an exceptional employer, offering a dynamic work environment in Summertown, Oxford, where employees can engage in meaningful projects that leverage advanced AI to address critical challenges in Defence and National Security. With a strong emphasis on personal and professional development, competitive compensation, and a collaborative culture, team members are empowered to shape their careers while making a tangible impact in the Air domain. The company's commitment to innovation and teamwork ensures that every employee has the opportunity to contribute to high-stakes missions alongside a supportive, multidisciplinary team.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer (m/w/d) in Oxford
✨Join Local Tech Meetups
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We think you need these skills to ace Machine Learning Engineer (m/w/d) in Oxford
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Mind Foundry.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Mind Foundry and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Mind Foundry
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Mind Foundry uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.