Machine Learning Engineer (Forward Deployed)
Machine Learning Engineer (Forward Deployed)

Machine Learning Engineer (Forward Deployed)

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead software deployments and create robust machine learning solutions for real-world challenges.
  • Company: Join a forward-thinking team at Mind Foundry, tackling Defence and National Security issues.
  • Benefits: Enjoy flexible hours, 25 days annual leave, private healthcare, and a dog-friendly office.
  • Other info: Opportunities for personal development and career growth in a supportive environment.
  • Why this job: Make a real impact with cutting-edge AI/ML technology in critical operational environments.
  • Qualifications: Degree in STEM or equivalent experience; strong programming skills in Python required.

The predicted salary is between 60000 - 80000 £ per year.

Security / Eligibility: 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.

Overview: 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. 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 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.

Key day-to-day activities:

  • Moving models from research/prototype to live, high-impact production environments, adapting those solutions to client-specific data, systems, and interfaces.
  • 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:

  • 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.
  • Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
  • Exceptional problem-solving skills and comfortable solving technical problems with limited internet access.

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).
  • Broader software engineering experience (e.g. Java, Node.js, React, PostgreSQL, system architecture, DevOps).

Note: 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:

  • 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
  • Workplace Nursery Scheme
  • Dog-friendly office!

Interview Process:

  • Initial discussion with the People team
  • TestDome coding exercise
  • 1 hour interview with two members of the Science & Engineering Team
  • 90 minute technical interview, including a 10 minute presentation and live coding exercise
  • In person meet the team at our Summertown office

Machine Learning Engineer (Forward Deployed) employer: Machine Learning Jobs UK

Mind Foundry is an exceptional employer that prioritises the growth and development of its employees, offering a supportive work culture where innovation thrives. Located in Summertown, Oxford, we provide flexible working arrangements, competitive benefits, and opportunities to engage with cutting-edge AI/ML technologies while contributing to national security. Our commitment to personal and professional development ensures that you will have the tools and support needed to excel in your role as a Machine Learning Engineer.
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Contact Detail:

Machine Learning Jobs UK Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Machine Learning Engineer (Forward Deployed)

✨Tip Number 1

Get to know the company inside out! Research Mind Foundry's projects and values, especially their work in Defence and National Security. This will help you tailor your conversations and show that you're genuinely interested in what they do.

✨Tip Number 2

Practice your technical skills before the interview. Brush up on Python, MLOps, and any other relevant tech. You might even want to run through some coding challenges to get your brain in gear for those live coding exercises!

✨Tip Number 3

Prepare to discuss real-world applications of your work. Think about how you've tackled complex problems in the past and be ready to share specific examples. This will demonstrate your problem-solving skills and how you can adapt to client needs.

✨Tip Number 4

Don’t forget to ask questions during your interviews! Show your curiosity about the role and the team dynamics. It’s a great way to engage with the interviewers and also helps you figure out if this is the right fit for you.

We think you need these skills to ace Machine Learning Engineer (Forward Deployed)

Machine Learning
Python
Docker
Linux
CI/CD
MLOps
Cloud Platforms
Model Serving Architectures
Data Processing
Streaming (Spark, Kafka)
Microservices (Flask, FastAPI)
Interactive Visualisations (Streamlit, Plotly, Gradio)
Problem-Solving Skills
Communication Skills
Technical Expertise

Some tips for your application 🫡

Show Your Passion for AI/ML: Let us see your enthusiasm for machine learning and artificial intelligence! Share any personal projects or experiences that highlight your skills and interest in the field. This will help us understand why you're a great fit for our team.

Tailor Your Application: Make sure to customise your CV and cover letter to match the job description. Highlight relevant experiences and skills that align with what we’re looking for, especially those related to production environments and client interactions.

Be Clear and Concise: When writing your application, keep it straightforward and to the point. Use clear language to explain your technical skills and experiences, making it easy for us to see how you can contribute to our mission.

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates during the process!

How to prepare for a job interview at Machine Learning Jobs UK

✨Know Your Stuff

Make sure you brush up on your machine learning concepts and the specific technologies mentioned in the job description, like Python, Docker, and MLOps. Be ready to discuss your past projects and how they relate to the role.

✨Showcase Problem-Solving Skills

Prepare to share examples of how you've tackled complex problems, especially in challenging environments. Think about situations where you had to adapt quickly or troubleshoot issues with limited resources, as this will resonate well with the team.

✨Communicate Clearly

Practice explaining technical concepts in simple terms. You’ll need to engage with both technical and non-technical stakeholders, so being able to bridge that gap is crucial. Consider doing mock interviews with friends to refine your communication skills.

✨Engage with the Mission

Familiarise yourself with the company’s mission and the impact of their work in Defence and National Security. Be prepared to discuss how your values align with theirs and how you can contribute to their goals, showing genuine interest in the role.

Machine Learning Engineer (Forward Deployed)
Machine Learning Jobs UK

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