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.

As a Machine Learning Engineer, you will design, build and deploy models and algorithms that will power Multiverse’s 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.

Desired

• Experience with MLFlow, Metaflow and/or LangChain

• Working knowledge of education/skills sector

• Understanding of AI ethics, data protection and information security