Technical Trainer (AI Engineering)

Department: Product & Tech Location: Home-based, UK (with occasional travel to London office) Reports to: Training Delivery Team Lead Hours: 37.5 per week Salary: (Depending on experience) ### Role Overview Cambridge Spark is looking for a Data Science Trainer to deliver our gold-standard technical programmes. While your deep technical expertise will be primarily focused on our Level 6 AI Engineer pathway, this role offers the exciting opportunity to deliver training across our wider portfolio of multiple apprenticeship programmes and high-impact corporate training engagements. You’ll lead deep-dive, hands-on workshops that empower data professionals and software engineers to build, test, and deploy robust machine learning models and advanced analytics solutions. Working across funded apprenticeships and corporate training, you’ll ensure that programmes meet high standards for learner engagement, technical rigour, and applied workplace impact. ### Key Responsibilities - Deliver the Level 6 AI Engineer curriculum as your primary focus, while also leveraging your expertise to lead advanced technical modules across other apprenticeship pathways and execute bespoke corporate training engagements. - Deliver engaging, hands-on workshops enabling learners to build supervised and unsupervised learning models using libraries like Scikit-Learn, XGBoost, and statsmodels. - Facilitate technical deep dives covering neural networks, deep learning frameworks (TensorFlow/PyTorch), and classical Natural Language Processing techniques. - Instruct learners on writing production-ready code, version control (Git), unit testing, and applying MLOps principles using cloud platforms (AWS, Azure, or GCP). - Facilitate high-quality, interactive training sessions via virtual platforms (our primary model), while maintaining the pedagogical flexibility to travel to client sites or hubs for face-to-face workshops when requested. - Partner with Product Managers to provide technical feedback on curriculum resources, Jupyter Notebook labs, and self-directed learning paths, building complex datasets for modelling. - Implement quality processes as defined by the Quality Team and maintain technical expertise across fast-moving ML frameworks, MLOps tooling, and software engineering best practices. ### Candidate Specification Essential - Exceptional hands-on experience building technical solutions in Python, including deep knowledge of the core data science ecosystem (Pandas, Scikit-Learn, etc.) and OOP principles. - Conceptual and mathematical understanding of predictive algorithms, model evaluation metrics, hyperparameter tuning, and bias/variance trade-offs. - Strong practical experience with Git, containerisation (Docker), CI/CD concepts, and deploying models as APIs or within cloud environments. - Familiarity with distributed computing and processing large datasets (e.g., PySpark, Databricks). - Exceptional communication skills with the ability to patiently explain complex mathematical and programmatic concepts to learners with varying baseline skills. Desirable - Demonstrable, hands-on experience working in a commercial industry setting applying these specific technical concepts. - Practical experience fine-tuning open-source LLMs (e.g., LLaMA, Mistral) or engineering with the Hugging Face ecosystem. - Certifications in AWS, Azure, or GCP data/ML specialities. - A formal teaching or training qualification (PGCE, QTS, or equivalent), or substantial enterprise facilitation experience. Company Benefits - Pension with 4% matched contributions, opportunity to opt into 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 - CPD Allowance alongside quarterly reflections to…