AI Instructor

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.

The Opportunity

We are seeking a passionate and knowledgeable AI Workshop Lead with working knowledge in training, tuning, deploying, and monitoring classical and deep Machine Learning models. As an AI Workshop Lead, you will be responsible for delivering high-quality curriculum and mentoring learners, guiding them professionally and will be involved in continuous improvement of relevant learning products.

You can expect to cover learning products such as AI & Machine Learning Fellowship and support delivering Machine Learning-related content in higher-level apprenticeship programmes such as Advanced Data Fellowship and AI Data Specialist. You will cover a range of topics, including:

• Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations)
• Solving Business Problems with Machine Learning
• Data Preparation and Feature Engineering
• Planning and preparing ML/AI solution
• Data Ethics and Responsible AI
• Model Engineering and Training
• Model Evaluation and Deployment
• Monitoring, Maintenance, and Continuous Learning
• Data Security, Privacy, and Governance
• Stakeholder Communication and Documentation

The Multiverse coaching team is a diverse mix of industry experts, educators, and academics, working together to build the future of work. You will be part of this team, reporting to a Delivery Lead who will guide your development. To ensure a strong start, you will complete a 3-week onboarding programme, covering:

• Modern teaching methodologies - for a hands-on, engaging learning experience
• Technical upskilling - to align with the relevant apprenticeship standard
• Practical coaching opportunities - a rigorous, robust feedback process to get you ready to launch your programme

At the end of onboarding, you will be ready to support Multiverse apprentices, helping them develop technical expertise and industry-relevant skills relating to the ML domain and drive impact within their businesses.

Specifically, you will:

• Be responsible for the delivery of our technical content and supporting our apprentices in upskilling in these technical areas through workshops and drop-in sessions.
• Help apprentices develop the appropriate Knowledge, Skills & Behaviours throughout their programme.
• Confidently facilitate delivery sessions of our technical learning content, ensuring the session delivers against learning objectives within the allotted time.
• Adhere to the Coach Quality framework to ensure a consistent level of quality for every session and a consistent experience for every apprentice.
• Create a vibrant, inclusive, and motivating environment that drives apprentice learning, engagement, and overall satisfaction.
• Moderate assignments in line with mark schemes to ensure quality and consistency while providing feedback and feedforward for apprentices to develop their technical and durable skills continually.
• Maintain an owner's mentality, whether assigned a learner or in support of other coaches, being proactive in taking action, sharing feedback, or providing support to ensure the progress and success of learners.
• Regularly liaise with coaches to align on apprentice interventions to ensure successful completion of the programme.
• Coordinate with cohort coaches and operations members to align on apprentice development and progress.
• Utilise resources & learning opportunities provided by Multiverse, stay up-to-date on knowledge, learning, and product updates, to ensure you are equipped to support your apprentices.
• Build & maintain credibility with your apprentices by utilizing a mixture of professional experience, program/domain/industry knowledge, and client context in your interactions.
• Create a compelling narrative about Multiverse, our mission, and the pillars of our offering, and help apprentices connect to it through the duration of their apprenticeship, and beyond.

About you:

You will have a combination of both deep technical skills and significant experience applying this in an industry setting, and ideally 1 year of experience in learning & development, coaching or education.

Technical Expertise:

• Postgraduate qualification in Computer Science, AI, Data Science, or related fields.
• Strong knowledge of AI, machine learning, deep learning, and probabilistic modeling.
• Proficient in Python, PySpark, data modeling, and microservices.
• Experience in MLOps, AI lifecycle management, and LLM orchestration on cloud platforms (AWS, GCP, Azure).
• Familiar with DevOps tools (Azure DevOps, GitHub Actions, Jenkins, Terraform, AWS CloudFormation).

Industry Experience:

• Hands-on experience with cloud-based AI/ML solutions and Responsible AI practices.
• Skilled in real-world ML applications and their societal impact.
• Proven ability to manage stakeholders at all levels and lead AI/ML projects.

Teaching & Communication:

• Experienced in technical training, mentoring, and coaching.
• Teaching qualification or industry recognition (e.g., FHEA) is a plus.
• Public speaking, industry engagement, and GitHub contributions are desirable.

Other Qualifications & Experience:

• Exceptional interpersonal, leadership, and communication abilities, with a demonstrated capacity to work across teams, lead cross-functional projects, and communicate complex technical concepts to non-technical stakeholders.
• Strong written and on-camera communication and presentation abilities, adept at engaging and motivating learners.
• Demonstrated skills in applying business case principles and articulating the business value related to relevant innovations.

You are passionate about delivering the best learning opportunities and supporting others on their development journey. You align closely with our values and can share examples of how you have demonstrated them.

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.

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.