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Cambridge Spark is looking for a Technical Trainer to deliver our gold-standard data and AI education programmes. You’ll lead practical, hands-on technical workshops, support learners through teaching and learning, and help shape the next generation of AI professionals. Working across both funded apprenticeships and corporate training, you’ll play a key role in ensuring our programmes meet high standards for technical depth, learner engagement, and real-world application.
Job Responsibility:
Deliver engaging technical workshops in Data Analysis, Machine Learning, and AI Engineering using Python and modern ML libraries
Teach and demonstrate applied skills across the end-to-end ML lifecycle, from data preparation to production deployment
Adapt sessions for learners from diverse professional and educational backgrounds
Contribute to curriculum improvement through content creation, updates, and assessment design
Maintain accurate learner progress records and engage in Quality Assurance activities
Collaborate with colleagues to share best practices and ensure consistency in delivery
Uphold safeguarding, compliance, and data privacy standards
Engage in ongoing CPD to enhance both technical expertise and teaching practice
Requirements:
Strong hands-on expertise with Python and its ML ecosystem (NumPy, pandas, scikit-learn, PyTorch)
Ability to build, evaluate, and tune ML models, including regression, classification, clustering, and ensemble methods
Practical experience with neural networks and deep learning (ANNs, CNNs, RNNs) and related optimisation techniques
Working knowledge of MLOps — deploying, versioning, monitoring, and maintaining models in production environments
Experience with Generative AI, NLP and Large Language Models (LLMs), including fine-tuning and secure API integration
Confident communicator able to explain technical concepts clearly to diverse audiences
Collaborative, organised, and committed to learner success
Nice to have:
Teaching qualification (PGCE, QTS, or equivalent)
2+ years’ experience teaching, training, or mentoring in a technical domain (e.g. data science, AI, analytics)
Understanding of explainability, fairness, and responsible AI — including use of SHAP, bias mitigation, and model cards
Awareness of cybersecurity, compliance, and sustainability considerations for ML systems
Experience developing curriculum content, assessments, or learning resources
Familiarity with apprenticeship delivery models and KSB frameworks
Knowledge of structured ML project methodologies such as CRISP-ML(Q) and agile collaboration in data teams
What we offer:
Remote first company providing flexibility to work from home
Pension with up to 5% matched contributions
Opportunity to opt into our salary sacrifice scheme
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
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