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:
1. Machine learning algorithms (supervised, unsupervised, reinforcement learning)
2. Assessing Security, Ethics & XAI
3. Developing & Testing AI Solutions
4. Leading AI & Future Innovation
5. Deep learning (CNNs, RNNs, transformers)
6. Generative AI and LLMs (e.g., GPT, BERT, Diffusion models)
7. Data preprocessing, feature engineering, model evaluation
8. AI deployment and MLOps best practices
9. Guide learners through coding labs, projects, and capstone work using Python, TensorFlow, PyTorch, or similar tools.
10. Stay updated with the latest AI technologies, tools, and trends to continuously improve training content.
11. Assess participant progress through quizzes, assignments, and evaluations.
12. Collaborate with curriculum developers and other trainers to maintain a consistent and high-quality learning experience.
13. Data architecture, pipelines and storage
14. Awareness of cutting-edge AI topics (e.g. agents, RAG, RAC, MCP)
15. Data visualisation
Skills & Abilities
Essential:
16. Bachelors or master’s degree in Computer Science, Data Science, AI, or related field.
17. Strong programming skills in Python and familiarity with tools like Jupyter, NumPy, pandas, scikit-learn, TensorFlow, and PyTorch.
18. Excellent communication, presentation, and facilitation skills.
19. Must be able to inspire and engage on AI topics
20. Practical expertise with building and deploying AI models'
Desirable:
21. Experienced in training, mentoring, or teaching technical content to professionals or students.
22. 3+ years of experience in AI/ML engineering or research.
23. Teaching qualification or willingness to work towards one
24. Understanding of Docker, Streamlit, FastAPI and Flask
25. Experience pandas, scikit-learn