Machine Learning Platform Engineer
Oak National Academy
- Closing: 12:00pm, 20th Nov 2026 GMT
Perks and benefits
Flexible working hours
Work from home option
Retirement benefits
Life Insurance
Employee Assistance Programme
Additional parental leave
Enhanced maternity and paternity leave
Paid emergency leave
Extra holiday
Professional development
Mentoring/coaching
Payroll giving
Team social events
Equipment allowance
Candidate happiness
8.55 (8118)
8.55 (8118)
Job Description
Machine Learning Platform Engineer
Remote (UK-based) | Full-time | Salary: £65,358 + benefits including 4.5-day week and 11% employer pension
Do your best work, for the right reasons.
We’re looking for a Machine Learning Platform 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.
Our culture has been independently recognised through:
Flexa verified (93% overall score, including 95% for working hours and 97% for role modelling)
Escape the City's Top 1% Employers – based on anonymous colleague reviews of culture, development, and impact
Investors in People Gold - through external accreditation and colleague feedback
💡 About the Role
You’ll join our Engineering Platform team, which builds the foundations our engineers and product squads rely on to ship reliable, secure software. As our Machine Learning Platform Engineer, you’ll focus on the infrastructure that gets AI models deployed and running reliably in production, from model management and version control to orchestration and scaling.
This is a new role. We’re splitting the machine learning engineer role across two teams. You’ll lead the build, deploy and operate side, working closely with our Intelligence Platform team’s Machine Learning Engineer, who develops and evaluates the models themselves. They build the models; you make sure they can be deployed, scaled and trusted in production by the engineers and squads who use them.
You’ll also help shape how we work. That means moving deployment off local machines into repeatable, automated delivery, strengthening how we monitor our services, and setting standards for our emerging agent-engineering practices.
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:
Build, maintain and secure the infrastructure that lets Oak build, deploy and operate reliable software and AI systems to be highly available and accessible to the widest number of users that meet Government Digital Service standards.
Move deployment off local machines and into repeatable, automated delivery using CI/CD pipelines and infrastructure as code.
Manage, version and orchestrate models so that those developed by our Intelligence Platform team can be deployed, scaled and run reliably in production.
Lead the continuous improvement of the observability, performance and reliability of Oak’s platform and cloud services and support teams across engineering to use SLOs and SLAs effectively.
Maintain monitoring, logging and alerting so teams can understand service quality and resolve problems quickly.
Take an active role in the design and implementation of automation that speeds up development, secures systems or improves service quality.
Contribute to, and develop, Oak’s engineering standards, including our emerging agent-engineering practices.
Work in cross-functional and product-oriented squads with colleagues from across the organisation, as required.
Deputise for other members of the Platform team and take on other general responsibilities as required.
🌱 What we're looking for
You’ll have solid experience running cloud infrastructure in production, and a real interest in what it takes to run machine learning and AI systems well. This is a fast-moving field, so we don’t expect years of experience in it. If you’ve spent a few months deploying or operating models, or you’ve run comparable production systems and want to apply those skills to AI, we’d love to hear from you. Experience with event-driven architectures using serverless technologies such as Google Cloud Run, AWS Lambda or Azure Functions will help, but you can grow into some of this with us. What matters most is that you care about making models reliable, secure and easy for others to ship.
Beyond that, you'll bring:
Experience leading the continuous improvement of observability, monitoring and reporting solutions for complex cloud infrastructures.
Demonstrable experience deploying, orchestrating and operating machine learning or AI systems in production, or clear, transferable experience operating comparable production systems.
Proven experience of infrastructure-as-code practices, promoting reproducibility and consistency across cloud environments
Experience of security controls for cloud infrastructure and CI/CD pipelines, including secrets management, access control and least-privilege principles.
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
📖 See how we work
Want to know more about how we build our products? Our Engineering Substack shares how we build AI and data tools for education, including the decisions, trade-offs and lessons we've learned along the way. Read Oak's Engineering Substack - https://engineering.thenational.academy/
💛 Our Benefits
25 days annual leave, plus one extra day for each year of service (up to 28)
Additional Oak closure days over Christmas/New Year
11% employer pension contribution (with no minimum employee contribution)
A 36-hour working week, with half-days on Fridays or every other Friday off
Fully remote working - we’ll support your home set-up and offer coworking options if preferred
Twice-yearly in-person offsites to collaborate, connect, and have fun
A culture that genuinely supports flexibility, autonomy, and trust
🌈 Inclusion and Belonging
We believe diverse teams build better products. We warmly welcome applicants from all backgrounds, particularly those who 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.
We use the Applied platform to help reduce bias in our hiring process. Answers are anonymised and reviewed by a panel of humans.
📌 Key Info
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.
You’ll answer a few admin questions and some questions related to your day-to-day job. Your answers will go through our sift process: all answers will be anonymised, randomised, and then reviewed by a panel of reviewers (real humans), so it's your thinking that gets assessed, not your CV.
If you're shortlisted, we'll invite you to interview. We give everyone feedback at the end of the process.
Interview dates:
First stage interviews: Thursday 26 and Monday 30 November 2026
Technical Assessment interviews: Week commencing 7 December 2026
We are receiving excellent responses to our job advertisements. This may lead us to close the role early, so if you are considering applying, don't leave it too long to avoid missing out.
We are an equal opportunity employer.
We are committed to a policy of Equal Employment Opportunity and are determined to ensure that no applicant or employee receives less favourable treatment on the grounds of age, disability, gender reassignment, marriage and civil partnership, pregnancy and maternity, race, religion or belief, sex, or sexual orientation, or is disadvantaged by conditions or requirements which cannot be shown to be justifiable.
Removing bias from the hiring process
Removing bias from the hiring process
- Your application will be anonymously reviewed by our hiring team to ensure fairness
- You’ll need a CV/résumé, but it’ll only be considered if you score well on the anonymous review
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