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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.
Desired
Experience with MLFlow, Metaflow and/or LangChain
Working knowledge of education/skills sector
Understanding of AI ethics, data protection and information security
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 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.
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.
Company benefits
We asked employees of Multiverse what it's like to work there, and this is what they told us.
Working at Multiverse
Company employees
Gender diversity (male:female)
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Currently Hiring Countries
United Kingdom
United States
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