Forward Deployed Machine Learning Engineer

Mind Foundry
Oxford
1 week ago
Create job alert
Overview

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


#J-18808-Ljbffr

Related Jobs

View all jobs

Applied AI, Forward Deployed Machine Learning Engineer - EMEA

Senior Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Forward-Deployed Data Scientist II

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.