Applied AI Engineer

Multiverse is the upskilling platform for AI and Tech adoption.

We have partnered with 1,500+ companies to deliver a new kind of learning that's transforming today’s workforce.

Our upskilling apprenticeships are designed for people of any age and career stage to build critical AI, data, and tech skills. Our learners have driven $2bn+ ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.

In June 2022, we announced a $220 million Series D funding round co-led by StepStone Group, Lightspeed Venture Partners and General Catalyst. With a post-money valuation of $1.7bn, the round makes us the UK’s first EdTech unicorn.

But we aren’t stopping there. With a strong operational footprint and 800+ employees, we have ambitious plans to continue scaling. We’re building a world where tech skills unlock people’s potential and output.

Join Multiverse and power our mission to equip the workforce to win in the AI era.

The Opportunity

At Multiverse, we believe technology should empower everyone to achieve their potential. As an Applied AI Engineer, you’ll transform cutting-edge AI research into real-world products that make learning and development smarter, more personalised, and truly impactful for thousands of users. Join us to build intelligent features that shape the future of work and education.

Key Responsibilities

• Design & Deliver AI Solutions: Partner with Product, Design, and Data teams to shape and deliver AI-powered features that generate real impact to our learners, value for our customers, and align with Multiverse’s mission.

• Leverage Large Language Models (LLMs): Design, fine-tune, and integrate LLM-powered solutions for tasks such as content generation, semantic search, summarisation, and personalised learning experiences.

• Build & Integrate Models: Develop, fine-tune, and embed machine learning models into production systems using tools like Cursor and Gemini, ensuring they are fast, scalable, and dependable.

• Own the End-to-End Lifecycle: Take responsibility for the journey from raw data through experimentation, deployment to users, and continuous iteration.

• Measure What Matters: Track the performance, accuracy, and adoption of AI features, and use those insights to drive constant improvement.

• Enable Others: Share your expertise and make AI approachable, helping colleagues across teams see how it can enhance their work.

• Lead in MLOps & Cloud Infrastructure: Build robust pipelines for model training, deployment, and monitoring using AWS cloud services and modern MLOps best practices.

• Champion Innovation: Keep us ahead of the curve by exploring new AI tools, including Cursor and Gemini, and applying them to create exceptional user experiences.

About you

• Hands-On AI/ML Expertise: You’ve built and deployed machine learning models using frameworks like PyTorch, TensorFlow, or scikit-learn.

• LLM Expertise: Experienced in working with large language models (e.g., GPT, Claude, Gemini Pro) for production use cases, including prompt engineering, evaluation, and safety & inclusivity considerations.

• Strong Engineering Skills: Proficient in Python and TypeScript, with experience building APIs, microservices, and cloud-native applications.

• Experience with AI Tools: Familiarity with emerging AI tooling platforms such as Cursor and Gemini is highly desirable.

• Cloud & MLOps: Practical experience deploying AI solutions on AWS, with a strong grasp of CI/CD for models, version control, observability, and retraining pipelines.

• Data Skills: Skilled at working with structured and unstructured data, applying preprocessing and feature engineering techniques.

• User Focus: You can translate complex AI capabilities into product experiences that feel effortless and intuitive.

• Collaborative Approach: You work best in creative and cross-functional teams and thrive when building together.

• Growth Mindset: You’re curious, open to feedback, and excited to share what you learn while contributing to an inclusive, high-performing culture.

Benefits

• Time off - 27 days holiday, plus 5 additional days off: 1 life event day, 2 volunteer days, 2 company-wide wellbeing days (M-Powered Weekend) and 8 bank holidays per year

• Health & Wellness- private medical Insurance with Bupa, a medical cashback scheme, life insurance, gym membership & wellness resources through Wellhub and access to Spill - all in one mental health support

• Hybrid work offering - for most roles we collaborate in the office three days per week with the exception of Coaches and Instructors who collaborate in the office once a month

• Work-from-anywhere scheme - you'll have the opportunity to work from anywhere, up to 10 days per year

• Space to connect: Beyond the desk, we make time for weekly catch-ups, seasonal celebrations, and have a kitchen that’s always stocked!

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.

Our Commitment to Safeguarding

Multiverse is committed to safeguarding and promoting the welfare of our learners. We expect all employees to share this commitment and adhere to our Safeguarding Policy, our Prevent Policy and all other Multiverse company policies. Successful applicants will be required to undertake at least a Basic check via the Disclosure Barring Service (DBS).

For roles that will involve a Regulated Activity, successful applicants must also undergo an Enhanced DBS check, including a Children’s Barred List check and a Prohibition Order check. Roles involving Regulated Activity may interact with vulnerable groups, therefore are exempt from the Rehabilitation of Offenders Act 1974 meaning applicants are required to declare any convictions, cautions, reprimands, and final warnings.

Providing false information is an offence and could result in the application being rejected or summary dismissal if the applicant has been selected, and possible referral to the police and the DBS.