At a Glance
- Tasks: Lead the deployment of AI/ML systems, translating user needs into robust solutions.
- Company: Join a supportive team at Mind Foundry, tackling real-world challenges in Defence and National Security.
- Benefits: Enjoy hybrid working, flexible hours, private healthcare, and a competitive salary package.
- Other info: Dynamic environment with opportunities for personal and professional growth.
- Why this job: Innovate at the forefront of applied machine learning and make a real impact.
- Qualifications: Degree in STEM or equivalent experience; strong programming skills in Python required.
The predicted salary is between 36000 - 60000 £ per year.
We’re looking for a Forward Deployed Machine Learning Engineer to join a supportive, multidisciplinary team delivering real-world AI/ML systems into operational environments. In this role, you’ll lead 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. 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.
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.
Key day-to-day activities:
- Adapting solutions to client-specific data, systems, and interfaces by optimising data pipelines, training workflows, and inference paths for performance, scalability, and reliability.
- Resolving unforeseen edge cases and challenges, providing on-site fixes or relaying them back to the product team.
- Troubleshooting integration issues with existing systems.
- Working directly with product teams to maintain deep technical expertise in Mind Foundry's products, capabilities and workflows.
- Engaging directly with defence customers to translate their needs and goals into technical requirements.
- Providing hands-on support to end users.
- Extending and improving internal ML platforms, tooling, and best practices, incorporating learnings from deployments back into shared frameworks.
Core Skills & Experience:
- 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.
- Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
- Exceptional problem-solving skills and comfortable working in ambiguous, fast-moving environments, often embedded with customers or delivery teams.
Nice to Have:
- 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).
- Hands-on experience with production infrastructure, including Docker, Linux, CI/CD, MLOPs, cloud platforms, and model serving architectures.
- Broader software engineering experience (e.g. Java, Node.js, React, PostgreSQL, system architecture, DevOps).
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.
What do we offer?
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
- 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
- Home Office Setup Allowance
- Dog-friendly office!
For more information, please visit our website www.mindfoundry.ai or email recruitment@mindfoundry.ai
Forward Deployed Machine Learning Engineer in Oxford employer: Mind Foundry
Mind Foundry is an exceptional employer that prioritises the growth and development of its employees, offering a supportive work culture where innovation thrives. With a focus on applied AI in Defence and National Security, team members are empowered to tackle complex challenges while enjoying benefits like hybrid working, flexible hours, and a competitive compensation package. The Summertown, Oxford office fosters collaboration and creativity, making it an ideal environment for those looking to make a meaningful impact in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Forward Deployed Machine Learning Engineer in Oxford
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who’s already in the field. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning. Whether it’s GitHub repos or a personal website, having tangible evidence of your work can really set you apart when you’re chatting with potential employers.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios. Think about how you’d tackle real-world problems that might come up in the role. The more you rehearse, the more confident you’ll feel when it’s time to shine!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from candidates who are genuinely interested in joining our team. Plus, it gives you a chance to showcase your enthusiasm for the role right from the start.
We think you need these skills to ace Forward Deployed Machine Learning Engineer in Oxford
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight how your skills and experiences align with the role of a Forward Deployed Machine Learning Engineer. We want to see how you can tackle real-world AI/ML challenges, so don’t hold back on showcasing relevant projects!
Show Off Your Technical Skills:Since this role requires strong programming skills, be sure to include specific examples of your proficiency in languages like Python. We love seeing clean, reproducible code, so if you have any GitHub repos or projects, link them up!
Communicate Clearly:You’ll need to explain complex technical concepts to various audiences, so make sure your application reflects your ability to communicate effectively. Use clear language and avoid jargon where possible – we’re looking for clarity over complexity!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining our team at Mind Foundry!
How to prepare for a job interview at Mind Foundry
✨Know Your Tech Inside Out
Make sure you’re well-versed in the programming languages and tools mentioned in the job description, especially Python. Brush up on your knowledge of data processing, microservices, and any relevant frameworks like Flask or FastAPI. Being able to discuss your technical skills confidently will show that you’re ready to tackle the challenges of the role.
✨Understand the Client's Needs
Since this role involves working closely with defence customers, take some time to research their specific needs and challenges. Think about how your skills can translate into solutions for them. Being able to articulate how you can adapt machine learning solutions to meet client-specific requirements will set you apart.
✨Prepare for Problem-Solving Questions
Expect to face questions that assess your problem-solving abilities, especially in ambiguous situations. Prepare examples from your past experiences where you successfully navigated complex challenges or resolved unforeseen issues. This will demonstrate your capability to thrive in fast-moving environments.
✨Communicate Clearly and Effectively
Practice explaining complex technical concepts in simple terms, as you’ll need to communicate with both technical and non-technical audiences. During the interview, focus on clarity and ensure you’re engaging with your interviewers. This skill is crucial for translating user needs into technical requirements.