Machine Learning Engineer

Machine Learning Engineer

Full-Time 63000 - 77000 £ / year (est.) Remote
Oak National Academy Limited

At a Glance

  • Tasks: Lead the development and evaluation of machine learning models for impactful educational products.
  • Company: Join a mission-driven, fully remote not-for-profit focused on improving education.
  • Benefits: Enjoy a competitive salary, 4.5-day work week, and generous pension contributions.
  • Other info: Flexible work culture with opportunities for professional growth and team collaboration.
  • Why this job: Make a real difference in education while working with cutting-edge AI technology.
  • Qualifications: Hands-on experience with machine learning models and a passion for responsible AI.

The predicted salary is between 63000 - 77000 £ per year.

Salary £65,358 (GBP) + benefits (including 4.5 day week and 11% employer pension)

Seniority Mid-level

Perks and benefits:

  • Work from home option
  • Life Insurance
  • Employee Assistance Programme
  • Additional parental leave
  • Enhanced maternity and paternity leave
  • Paid emergency leave
  • Mentoring/coaching
  • Payroll giving
  • Team social events

Job Description:

Remote (UK-based) | Full-time | Salary: £65,358 + benefits including 4.5-day week and 11% employer pension

We’re looking for a Machine Learning Engineer to help us build beautifully simple, high-impact digital products that support teachers and improve outcomes for pupils across the UK. Oak is a fully remote, mission-driven organisation offering high levels of flexibility, autonomy, and purpose. We’re a national not-for-profit working in partnership with teachers to create the highest-quality, sequenced curriculum and lesson resources for pupils across all subjects and age groups.

About the Role:

You’ll join our Intelligence Platform team, which uses our curriculum and data expertise to improve our products and keep our AI high-quality and safe. As our Machine Learning Engineer, you’ll focus on the methodology behind the models that power our products and our shared evaluation service. That means turning product and user needs into well-posed problems, choosing and justifying the right data and techniques, and designing the evaluation that tells us whether a model is working.

This is a new role. We’re splitting the traditional machine learning engineer role across two teams. You’ll lead the develop, train and evaluate side, working closely with our Engineering Platform team’s Machine Learning Platform Engineer, who owns the infrastructure that deploys and runs models. You’ll also work with our Software Engineers, who build the application code that brings models into our products.

Teachers rely on our AI-powered tools, so evaluation, safety and responsible AI sit at the heart of this role. You’ll work with EdTech partners and the DfE on AI quality and safety. You’ll also help turn our curriculum and data expertise into reusable models and insight services that others can build on.

As part of the Oak team, you'll contribute to the wider success and culture of the organisation, and support and role model our five values: create the right environment, be a great colleague, own your role but work for the team, make things happen, and keep getting better.

What you'll be doing:

  • Lead the continuous improvement of Oak’s machine learning models and AI systems, working with Machine Learning Platform Engineers and Software Engineers to take them into production.
  • Coordinate the scoping of machine learning and AI problems, translating product and user needs into the right data and techniques.
  • Choose and justify appropriate statistical, machine learning and AI techniques for different problems, and keep evaluating new tools and methods.
  • Design the evaluation that assesses and improves our models, including automated testing and assurance of AI systems.
  • Contribute to Oak’s shared AI evaluation, quality and safety services, including moderation and threat detection.
  • Help turn Oak’s curriculum and data expertise into reusable models and insight services that internal teams and the wider ecosystem can build on.
  • Engage with EdTech partners and the DfE on AI evaluation, quality and safety.
  • Share knowledge and provide guidance to less experienced colleagues.
  • Work in cross-functional and product-oriented squads with colleagues from across the organisation, as required.
  • Deputise for other members of the Intelligence Platform team and take on other general responsibilities as required.

What we're looking for:

You’ll have hands‑on experience developing and evaluating machine learning or AI models, and a clear sense of how to pick the right approach for a problem, not just the newest one. This field moves quickly, so we don’t expect years of experience with every technique. If you’ve spent a few months building and evaluating models, or you’re coming from data science or software engineering and want to go deeper into machine learning, we’d love to hear from you.

What matters most is that you care about making AI safe, fair and useful for teachers and pupils, and that you can explain your choices to people who aren’t specialists.

Beyond that, you'll bring:

  • Experience in leading the continuous improvement of machine learning models or AI systems, from development into production.
  • Knowledge of machine learning frameworks and cloud-based machine learning tools.
  • Experience in designing and running evaluation of model performance, including assurance of AI systems.
  • Knowledge of responsible AI principles, including fairness, bias detection and privacy-preserving data practices.
  • Desire to build beautiful, easy-to-use digital products with an understanding of the importance of accessibility in all its forms.
  • Strong communication skills and a collaborative approach to working across teams.

The successful candidate will have a desire to contribute across all areas to ensure Oak's success. You will be comfortable moving quickly and with agility, and be confident working with a range of digital systems (including proprietary ones, as required). You will continually look for ways that the team can keep getting better. You will be excellent at working as part of a remote team, building relationships and managing your time effectively.

Inclusion and Belonging:

We believe diverse teams build better products. We warmly welcome applicants from all backgrounds, particularly those that are underrepresented in the tech and education sectors. If you're from an underrepresented group, there's a good chance you're discounting yourself before you've even started. That's more common than you'd think, and it means we may miss out on brilliant people. If you're excited by this role but don't meet every requirement, please apply anyway.

Location: Remote, but you must be based in the UK with the legal right to work here.

Sponsorship: Unfortunately, we’re unable to offer visa sponsorship at this time.

Closing date: Friday 20 November 2026 (We’ll be reviewing applications as they come in and may close the role early).

If this sounds like the kind of role and team where you could do your life’s best work, we’d love to hear from you.

Machine Learning Engineer employer: Oak National Academy Limited

Oak is an exceptional employer, offering a fully remote, mission-driven environment that prioritises flexibility, autonomy, and meaningful impact in education. With a strong commitment to employee well-being, including a 4.5-day work week, generous pension contributions, and opportunities for professional growth, Oak fosters a collaborative culture that values diverse perspectives and encourages innovation. Join us to make a real difference in the lives of teachers and pupils across the UK while enjoying a supportive and inclusive workplace.

Oak National Academy Limited

Contact Details:

Oak National Academy Limited Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Machine Learning Engineer

✨Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Oak National Academy Limited or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

✨Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Oak National Academy Limited.

✨Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Oak National Academy Limited.

✨Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Oak National Academy Limited that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Machine Learning Engineer

Machine Learning
AI Model Development
Model Evaluation
Statistical Techniques
Cloud-based Machine Learning Tools
Responsible AI Principles
Bias Detection

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 Oak National Academy Limited.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Oak National Academy Limited 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 Oak National Academy Limited

✨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 Oak National Academy Limited 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.