Learning Designer

Cambridge Spark
Liverpool
2 weeks ago
Applications closed

Related Jobs

View all jobs

Learning Designer

Contract Machine Learning Engineer, mostly remote

AI) Machine Learning Research Engineer

Front End Developer

Software Engineers

Innovation Developer

Department:Product and Technology

Location: Home based, UK (with occasional travel to our London office)

Reports to:Director of Curriculum

Hours: 37.5 per week

Salary: (Depending on experience)

Role Overview

As a Learning Designer at Cambridge Spark, you will transform content into engaging learning materials. You will focus on building effective learning modules within our platform, working closely with SMEs and Product Managers, you will ensure gold-standard learner experiences while maintaining accessibility standards and incorporating learner feedback.

Key responsibilities:

  • Content Development: Convert technical content developed by data and AI subject matter experts into engaging, accessible learning materials that bring complex concepts to life
  • Learning Material Design: Design visually compelling, instructionally sound learning materials that effectively communicate concepts to diverse audiences
  • Learning Module Development: Build comprehensive modules within our learning platform, incorporating various elements to create cohesive learning journeys
  • Stakeholder Collaboration: Work closely with SMEs and Product Managers to ensure technical accuracy while maintaining engaging and accessible learning experiences
  • Feedback Implementation: Implement learner feedback related to design and user experience, continuously improving our data and AI training materials
  • Accessibility: Ensure all learning materials meet accessibility standards, making appropriate accommodations for diverse learner needs across our technical curriculum

Candidate Specification:

Essential

  • Experience in instructional or learning design, preferably within technical or STEM disciplines
  • Strong digital design skills with proficiency in Google Workspace and Canva or equivalent
  • Experience with AI-powered tools and technologies, with a focus on improving efficiency and decision-making
  • Experience of storyboarding and developing video learning materials
  • Experience building modules within learning management systems or educational platforms
  • Understanding of adult learning principles and how to apply them to technical content
  • Experience designing learning materials for learners with special educational needs
  • Excellent visual communication skills and ability to present complex information clearly
  • Strong collaborative abilities to work effectively with technical subject matter experts
  • Meticulous attention to detail and commitment to producing high-quality learning assets
  • Knowledge of accessibility standards and their implementation in digital learning materials
  • Ability to manage multiple projects simultaneously in a fast-paced environment

Desirable

  • Experience building materials for apprenticeship programmes
  • Experience of executive education programme design

Company Benefits:

  • Remote first company providing flexibility to work from home
  • Pension with up to 5% matched contributions
  • 25 days holiday + Flexi bank holidays + 1 day off on your birthday
  • A day for volunteering
  • Enhanced Maternity and Paternity Leave
  • Health & Wellbeing allowance of up to £30 per month
  • Annual Summer and Xmas events
  • Company socials including everything from Cambridge College formals, pub nights to team building events
  • CPD Allowance
  • Private medical insurance and cash plan
  • Holiday buy back scheme (up to 10 days p/a)
  • EAP with 24 hour confidential support line

Background to our Organisation

We are an education technology company that enables corporate and government organisations to achieve their business goals by educating their workforce with critical digital transformation skills to succeed in the AI era.

We deliver unique and innovative professional education that is accelerating the digital transformation of our clients, advancing the careers of their employees, helping people get into work and closing the digital skills gap. We are in a sector that is crucial to the economy and workforce, with a lot of opportunity for change and innovation. We are at the cutting edge of teaching applied data and digital skills, with our unique patented learning platform EDUKATE.AI offering our clients and learners a unique learning experience. EDUKATE.AI was developed with support from Innovate UK and provides all of our learners with 24/7 immediate feedback on their work, helping accelerate the learning process and providing a sandbox environment to experiment on real world datasets.

Since 2016, we have supported more than 15,000 learners across four continents with nearly 550,000 pieces of code submitted for feedback on EDUKATE.AI. We are trusted by some of the most recognisable brands in the world to educate their workforce, including Microsoft, the NHS, GSK, easyJet, the BBC and John Lewis. Our focus on applied learning to create business impact sets us apart - individual learners have reported applying their skills at work to generate recorded value of up to £40m.

Values

At the centre of the way we work together and inspire each other to achieve success are these core values:

Entrepreneurial

We take initiative and show entrepreneurial spirit which fuels innovation at Cambridge Spark. This includes identifying opportunities for improvement, taking ownership for implementing solutions effectively and driving improvement by using proof of concepts to demonstrate the feasibility and value of their work.

Team Spirit

Everyone is part of building an open and transparent culture, communicating effectively to raise issues, discuss improvements and share the evidence used to make decisions.

Customer-focused

Our customers are at the centre of everything we do, inspiring us to create great work. We strive to build friendly, professional and lasting relationships with them to better understand and anticipate their needs.

Gold Standard

We are experts in our field and are constantly developing our technology and offering. We set the benchmark in our industry: both in what we offer customers and in how we deliver it.

____________________________________________________________________________

Cambridge Spark is an Equal Opportunities Employer and prohibits discrimination and harassment of any kind. Cambridge Spark is committed to the principle of equal employment opportunities for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at Cambridge Spark are based on business needs, job requirements and individual qualifications, without regard to race, colour or ethnicity, ability or disability, gender or gender reassignment, sexual orientation, marital status, religion, age or any other status protected by the laws or regulations in the locations where we operate. Cambridge Spark will not tolerate discrimination or harassment based on any of these characteristics. Cambridge Spark encourages applicants of all ages.

Powered by JazzHR

Pnxc7ZtTra

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.

Machine Learning vs. Deep Learning vs. MLOps Jobs: Which Path Should You Choose?

Machine Learning (ML) continues to transform how businesses operate, from personalised product recommendations to automated fraud detection. As ML adoption accelerates in nearly every industry—finance, healthcare, retail, automotive, and beyond—the demand for professionals with specialised ML skills is surging. Yet as you browse Machine Learning jobs on www.machinelearningjobs.co.uk, you may encounter multiple sub-disciplines, such as Deep Learning and MLOps. Each of these fields offers unique challenges, requires a distinct skill set, and can lead to a rewarding career path. So how do Machine Learning, Deep Learning, and MLOps differ? And which area best aligns with your talents and aspirations? This comprehensive guide will define each field, highlight overlaps and differences, discuss salary ranges and typical responsibilities, and explore real-world examples. By the end, you’ll have a clearer vision of which career track suits you—whether you prefer building foundational ML models, pushing the boundaries of neural network performance, or orchestrating robust ML pipelines at scale.