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.

As a Machine Learning Engineer, you will design, build and deploy models and algorithms that will power Multiverse’s external customer-facing product features and internal data products. 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 Data & Insight team, working closely with Data Scientists, ML Ops Engineers, Data Product Managers, Data Engineers, Insight Analysts. 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:

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

• Develop prototypes based on cutting-edge applied machine learning working on video, audio, text, and structured data sources.

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

• Productionize and operate ML models and pipelines at scale.

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

• Design and implement machine learning infrastructure capabilities.

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

• 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.

What we’re looking for:

Required

• 2+ years of machine learning engineering experience (e.g. writing ML code for production systems)

• In-depth experience with Python and strong command of data structures and algorithms in order to contribute to production-grade code.

• Proficiency in engineering best practices (CI/CD, observability, configuration management)

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

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

• Working knowledge of PostgreSQL

• Experience with version control (e.g. GitHub)

• Experience working within a cloud environment (e.g. AWS)

• Understanding of AI ethics, data protection and information security

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

• Meticulous attention to detail

• A growth mindset and a desire to continuously develop

• Commitment to Multiverse’s mission and values

Desired

• Experience with MLFlow, Metaflow and/or LangChain

• Working knowledge of education/skills sector

Benefits

• 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 visits to the London office

• 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.

Safeguarding

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.