Applied AI Engineer Job at Multiverse (London)

Job Description

At Multiverse, we believe technology should empower everyone to achieve their potential. As a Senior member of the Applied AI team, you will sit at the intersection of data science and software engineering. You won’t just build models in isolation; you will transform cutting-edge AI research into scalable, real-world products that make learning and development smarter and more personalised for thousands of users. You will play a pivotal role in steering our AI roadmap, guiding collaborative efforts across product and engineering to shape the future of work and education.

Job Responsibility

Design & Deliver AI/ML solutions: Translate complex stakeholder queries and business hypotheses into actionable experiments and AI/ML model requirements
Architect LLM & Agentic Workflows: Design and integrate LLM-powered solutions (e.g., GPT, Claude, Gemini) for content generation and personalized learning
Own the End-to-End Lifecycle: Take full ownership of the journey from data lineage and preprocessing through to experimentation, deployment, evaluation and continuous iteration
Experimentation Rigour & Quality: Proactively monitor and refine models to optimise effectiveness while minimising sampling/analytical biases and operational challenges
Lead in MLOps & Infrastructure: Build and maintain scalable pipelines for model training and deployment using AWS and modern MLOps practices
Strategic Influence & Mentorship: Bridge the gap between technical concepts and business objectives by communicating actionable insights to stakeholders

Requirements

5+ years of Data Science, Machine Learning, or AI Engineering experience, with a proven track record of leading complex AI/ML projects from concept to production
Proficient in Python and its ecosystem (e.g. NumPy, Pandas, Scikit-Learn, PyTorch)
Deep experience with LLM orchestration (e.g. Langchain) and prompt engineering
Advanced knowledge of SQL and experience working with both structured and unstructured data
Strong proficiency in building APIs and microservices
Comfortable with GitHub, CI/CD, observability & evaluation practices, and Infrastructure as Code (e.g., Terraform)
Practical experience deploying and monitoring AI solutions within AWS, Azure or similar cloud environments
Analytical Rigour with exceptional attention to detail regarding data lineage and bias
User-Product first approach
Growth Mindset

Nice to have

Familiarity with the education or skills sector
Experience with knowledge graphs and semantic web concepts

What we offer

27 days holiday, plus 5 additional days off: 1 life event day, 2 volunteer days, 2 company-wide wellbeing days and 8 bank holidays per year
private medical Insurance with Bupa
a medical cashback scheme
life insurance
gym membership & wellness resources through Wellhub
access to Spill - all in one mental health support
Hybrid work offering - for most roles we collaborate in the office three days per week
Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year
Space to connect: weekly catch-ups, seasonal celebrations, and a kitchen that’s always stocked

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Applied AI Engineer

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