Multiverse • Remote (UK)

Senior MLOps Engineer, UK

Employment type:  Full time

3–4 days/week at home

A little flex time

Job Description

We’re on a mission to create a diverse group of future leaders. We do that through professional apprenticeships because we believe learning on-the-job creates a more equitable and successful path to careers. We find, train and support talented individuals, wherever they are in their career journey, and equip them with the in-demand tech, software engineering, and data skills to transform their careers and deliver a better route to growth for their employers.

We’ve had some big achievements. We hit 10,000 apprentices in our community - and counting. We launched one of the largest data apprenticeship programs in the UK with Jaguar Land Rover, and we’ve partnered with companies like Mars, Verizon and CitiBank. Not to forget becoming a mission-driven EdTech unicorn after our $220m Series D.

But we aren’t stopping here. Join Multiverse and build the future of learning at work.

The Opportunity

As a Senior Machine Learning Operations (MLOps) Engineer, you will be responsible for developing and maintaining Multiverse’s Machine Learning pipeline - establishing, automating, optimising and securing data flows from, through and into multiple data sources that our Data Science team will use to serve all parts of the business via Machine Learning.

This role will be within the Data Engineering & Infrastructure team but will involve very close collaboration with our Data Science team. Both of these teams sit within our broader Data & Insight department, which also includes Data Product Management, Analytics Tools, Solutions and Insight teams. While your primary focus will be on MLOps, you will also be required to support the team with its broader Infrastructure & DevOps needs.

You will need to be methodical, analytical, creative and tenacious with very high attention to detail. And while this is a technical role, our team culture is one where everyone is expected to collaborate well and take ownership of both deliverable & stakeholder management.

What you’ll focus on:


  • Designing, automating, developing and maintaining our MLOps pipelines and processes to assist our Data Scientists in productionising their models

  • CI/CD, testing and monitoring of models

  • Managing versions and experiment /registry tracking

  • Management of a Data Version Control system

  • Establishing and maintaining good governance practices for MLOps

Infrastructure Management

  • Managing deployment via an Infrastructure as Code (Terraform) approach of AWS and other relevant resources

  • Continuously monitoring system integrity and security risks

Integration and Security

  • Assist with monitoring system integrity/security risks and implementing remediations/upgrades as necessary

  • Participating in regular infrastructure security reviews and overseeing implementation of all resultant technical change requirements

  • Working with the Data Engineers to ensure that timely, concise and accurate data is fed to our Data Science Lab and is used appropriately.

Automation, Optimisation and Scalability

  • Designing, developing and maintaining automated systems and processes (e.g. via AWS) that enable greater operational efficiency at scale

  • Ensuring all of our infrastructure is scalable - including management of any associated technical upgrades - ahead of organisational growth trajectory

  • Continuously monitoring for data accuracy

What we’re looking for:


  • 3+ years of relevant MLOps experience

  • 3+ years experience of working with a Data Science team

  • 3+ years experience of working with Data Engineers

  • Proven track record of producing high quality Machine Learning deliverables against ambitious goals and deadlines

  • Pragmatic, ‘can-do’ approach with a demonstrable record of turning challenges into opportunities

  • Experience with AWS (inc RDS, S3, Athena, Sagemaker etc.), PostgreSQL, GitHub, CircleCI/Jenkins (or similar), ETL, CI/CD and Infrastructure as Code (e.g. Terraform)

  • Experience with model experiment tracking

  • Meticulous attention to detail

  • Commitment to Multiverse’s mission and values

Non-Required (But Desirable):

  • Experience with Asana (or similar) to manage quarterly/ongoing deliverables

  • Working knowledge of Python

  • Experience within education/skills sector


  • Time off - 27 days holiday, plus 7 additional days off: 1 life event day, 2 volunteer days and 4 company-wide wellbeing days

  • Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Gympass and access to Spill - all in one mental health support

  • Hybrid & remote work offering - with weekly or monthly visits to the London office and the opportunity to work abroad 45 days a year

  • Team fun - weekly socials, company wide events and office snacks!

Our commitment to Diversity, Equity and Inclusion

We’re an equal opportunities employer. And proud of it. Every applicant and employee is afforded the same opportunities regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. This will never change.


All posts in Multiverse involve some degree of responsibility for safeguarding. Successful applicants are required to complete a Disclosure Form from the Disclosure and Barring Service ("DBS") for the position. Failure to declare any convictions (that are not subject to DBS filtering) may disqualify a candidate for appointment or result in summary dismissal if the discrepancy comes to light subsequently.

Company benefits

Enhanced maternity leave
Enhanced paternity leave
Adoption leave
Work from anywhere scheme
27 days annual leave + bank holidays
Enhanced sick pay
Pregnancy loss leave
M-powered days - Company wide wellbeing days where the whole company shuts down once per quarter.

We asked employees of Multiverse how satisfied they were with flexible working, and this is what they told us

Employees are very happy with their working location freedom
Employees are largely happy with the flexibility in the hours they work
Employees are largely happy with the benefits their company offers
Work-life balance
Employees feel that they can switch off quite easily from work
Role modelling
Employees feel that most people work flexibly
Employees feel they have complete autonomy over getting their work done
Working at Multiverse

Company employees


Gender diversity (male:female)


Office locations

London, New York & Remote

Funding levels


Hiring Countries

United Kingdom
United States