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 1,000 leading companies including the likes of Microsoft, Citi and Just Eat to help solve their business-critical problems, and we’ve trained over 12,000 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.

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.