QA - Search results(2 vacancies/1)-Profile : Delivery-->Group Learning Technical

AI Engineering Trainer

Ref. : 1000008366
Home Based
Other
AI Engineering Trainer (Level 6) Home based About our role: We are seeking an experienced and passionate AI Engineer Apprenticeship Trainer to deliver high-quality, hands-on training in artificial intelligence and machine learning engineering. The ideal candidate will have a strong background in AI/ML concepts, software engineering, and real-world project experience, with a passion for teaching and upskilling professionals or students. Key Responsibilities Teach key topics including: Machine learning algorithms (supervised, unsupervised, reinforcement learning) Assessing Security, Ethics & XAI Developing & Testing AI Solutions Leading AI & Future Innovation Deep learning (CNNs, RNNs, transformers) Generative AI and LLMs (e.g., GPT, BERT, Diffusion models) Data preprocessing, feature engineering, model evaluation AI deployment and MLOps best practices Guide learners through coding labs, projects, and capstone work using Python, TensorFlow, PyTorch, or similar tools. Stay updated with the latest AI technologies, tools, and trends to continuously improve training content. Assess participant progress through quizzes, assignments, and evaluations. Collaborate with curriculum developers and other trainers to maintain a consistent and high-quality learning experience. Data architecture, pipelines and storage Awareness of cutting-edge AI topics (e.g. agents, RAG, RAC, MCP) Data visualisation Skills & Abilities Essential: Bachelors or master’s degree in Computer Science, Data Science, AI, or related field. Strong programming skills in Python and familiarity with tools like Jupyter, NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Excellent communication, presentation, and facilitation skills. Must be able to inspire and engage on AI topics Practical expertise with building and deploying AI models' Desirable: Experienced in training, mentoring, or teaching technical content to professionals or students. 3+ years of experience in AI/ML engineering or research. Teaching qualification or willingness to work towards one Understanding of Docker, Streamlit, FastAPI and Flask Experience pandas, scikit-learn
B5 4UA

Computing Lecturer

Ref. : 1000008441
Home Based
Other
Computing Lecturer Home based Job Purpose As a Lecturer in the Degree Apprenticeship team in QAA you will be working with learners that are studying alongside full-time work to develop themselves in their professional specialism. We teach using Blended Learning, which means that our Lecturers support learners through the development of online content and activities, remote interactive sessions (e.g. WebEx or discussion forums) and in live-online or Face-to-Face workshop. The role of a Lecturer includes delivery of workshops, marking and module leadership. Role Responsibilities: To design and take ownership for multiple modules on the Degree Apprenticeship programmes, and to contribute to the delivery of high quality learning. This will include online support throughout the programme and delivery of a series of face-to-face live online workshops Development of course materials for a number of modules, including video for online learning, exercises, slides and assessments To contribute to the wider team activities on assessment and teaching as required. To make an active contribution to ensure continual programme improvements, and that all apprentices receive a high quality learning experience. Act as moderator and peer reviewer for other modules on a termly basis. Feedback from apprentices in evaluations judge the quality of learning to be “very satisfied” or “satisfied”, using the Satisfaction score calculation to ensure a target of a minimum of 90% is achieved. Teaching and learning practice are consistently judged to be ‘good’ or ‘ outstanding’ as part of the regular peer observations of teaching and learning. Your Experience/Skills Essential Qualifications: A post-graduate degree (MSc or similar) A teaching qualification or a desire to obtain one, preferably Fellowship of the Higher Education Academy Subject specific qualifications Desirable Qualifications: PhD or working towards one Teaching qualifications Ability to deliver practical and engaging teaching and learning sessions. Industry experience within subject area. Excellent, detailed knowledge of more than one topic within the required subject areas (e.g. IT PM, Computer Science, Business & Tech, Data Science). Knowledge of Apprenticeships and work-based learning, or knowledge of Higher Education. Understanding of equity and diversity issues.
B5 4UA

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