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Multiverse • London

Senior Machine Learning Engineer - UK, Hybrid

Employment type:  Full time

4 days/week at home

A little flex time

Apply now

Job Description

We’re on a mission to provide equitable access to economic opportunity, for everyone.

We close critical skill gaps in the workforce through a new kind of apprenticeship that combines work and learning. We begin by recognizing high-potential individuals both inside and outside of a company's current workforce and then we create applied, guided and equitable learning programs, with measurable impact. Because we believe the world needs a better way to match its potential.

We work with over 1,500 leading companies including the likes of Microsoft, Citi and Just Eat to help solve their business-critical problems, and we’ve trained over 16,000 professional apprentices in the tech and data skills of the future. This is made possible by our global team who are driven to achieve a mission that matters, together.

Join Multiverse and help us set a new course for work.

The Role

As a Machine Learning Engineer at Multiverse, you will design, build and deploy models and algorithms that will power our external customer-facing product experiences . You will leverage our unique data-sets to develop truly differentiated data science, machine learning & artificial intelligence- based assets, helping transform Multiverse into a true AI-first company.

This role will be within the AI Team, working closely with other ML Engineers, Data Scientists, ML Ops Engineers, Product Managers. The AI Team’s mission is to build the intelligence layer at Multiverse that fuels captivating educational experiences, drives effective and continuous digital transformation for enterprises, and empowers Multiverse coaches and operations with tools that scale our teaching capabilities.

You will also collaborate closely with key stakeholders from our Product, Engineering & other teams across the business - often working in cross-functional squads alongside experts from across other disciplines. You will need to be analytical, creative and collaborative, with a strong understanding of algorithm development and the ability to work within a fast paced team environment.

What you’ll focus on:

  • Partner with data scientists, engineers, and stakeholders across the organisation to define high-impact solutions and deliver high-quality systems and data pipelines.

  • Building, training & iterating on data science, machine learning & artificial intelligence models.

  • Develop prototypes based on cutting-edge applied machine learning, working with different data modalities.

  • Own the technical translation of state-of-the-art machine learning innovations to inform the development of new product features.

  • Productionise and operate ML models and data pipelines at scale.

  • Design and implement well-defined APIs for new machine learning tools to make them available for customers and engineering teams across the organisation.

  • Design and implement machine learning infrastructure capabilities.

  • Reviewing and validating scalable data collection and processing methods.

  • Tracking and understanding emergent trends.

  • Sourcing and leveraging external research/data that strengthen our internal insights.

People successful in this role likely:

  • Take a tenacious, curious, and pragmatic approach to problem solving, with a focus on generating usable and scalable outputs

  • Possess a meticulous attention to detail

  • Have a growth mindset and a desire to continuously develop

  • Feel connected and committed to Multiverse’s mission and values

Required Experience

  • Deep expertise in software engineering and machine learning engineering, gained from prior experience working on a production engineering team

  • Strong backend engineering ability and understanding of engineering best practices (CI/CD, version control, cloud environments, observability, configuration management)

  • In-depth experience with Python and strong command of databases (e.g. PostgreSQL), data structures, and algorithms

  • In-depth knowledge of one or more of the major machine learning frameworks (e.g., PyTorch or TensorFlow).

  • Ability to manage machine learning projects and clearly communicate outcomes to technical and non-technical audiences.


  • Experience with MLFlow, Metaflow and/or LangChain

  • Working knowledge of education/skills sector

  • Understanding of AI ethics, data protection and information security


  • 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. Read our Equality, Diversity & Inclusion policy here.


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

Health insurance – cover provided by Bupa
Work from anywhere scheme – work for up to 45 days/year abroad
27 days annual leave + bank holidays
Gym membership
Enhanced sick pay
Volunteer days – 2 days/year
Enhanced maternity leave
Enhanced paternity leave
Adoption leave
Pregnancy loss leave
Company shutdown periods
Mental health days
Cycle to work scheme
Faith rooms
Meditation space
Fully stocked snack cupboard
Life insurance
Salary sacrifice
Share options
Lunch and learns
Employee discounts
M-powered days - Company wide wellbeing days where the whole company shuts down once per quarter.
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

Awards & Achievements

Most flexible companies

Most flexible companies

Flexa100 2024
EdTech & Education

EdTech & Education

Industry awards 2023
Most flexible companies

Most flexible companies

Flexa100 2023

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