Technical Trainer (AI Engineering)

TL;DR

Technical Trainer (AI Engineering): Delivering high-impact technical programmes and workshops for AI engineers with an accent on machine learning models, MLOps, and production-ready code. Focus on instructing learners in supervised/unsupervised learning, deep learning frameworks, and deploying models within cloud environments.

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

Company

An education technology company that enables corporate and government organisations to achieve digital transformation through a patented AI learning platform, EDUKATE.AI.

What you will do

• Deliver the Level 6 AI Engineer curriculum and lead advanced technical modules across various apprenticeship pathways.
• Conduct hands-on workshops on building supervised and unsupervised learning models using Scikit-Learn, XGBoost, and statsmodels.
• Facilitate deep dives into neural networks, deep learning frameworks (TensorFlow, PyTorch), and NLP techniques.
• Teach production-ready coding standards, Git version control, unit testing, and MLOps principles on AWS, Azure, or GCP.
• Collaborate with Product Managers to refine curriculum resources, Jupyter Notebooks, and learning paths.
• Implement quality processes and maintain expertise in fast-evolving ML frameworks and software engineering practices.

Requirements

• Exceptional hands-on experience with Python, the data science ecosystem (Pandas, Scikit-Learn), and OOP principles.
• Strong mathematical understanding of predictive algorithms, model evaluation, and hyperparameter tuning.
• Practical experience with Git, Docker, CI/CD, and deploying models as APIs in cloud environments.
• Familiarity with distributed computing and processing large datasets using PySpark or Databricks.
• Must be based in the UK (Home-based with occasional travel to London).
• Excellent communication skills to explain complex concepts to learners of various skill levels.

Nice to have

• Commercial industry experience applying AI/ML concepts.
• Experience fine-tuning open-source LLMs (LLaMA, Mistral) or using the Hugging Face ecosystem.
• Certifications in AWS, Azure, or GCP data/ML specialties.
• Formal teaching qualification (PGCE, QTS) or extensive enterprise facilitation experience.

Culture & Benefits

• Pension with 4% matched contributions and salary sacrifice options.
• 25 days holiday plus flexible bank holidays and a birthday off.
• Health & Wellbeing allowance (£30/month) and private medical insurance.
• Dedicated CPD allowance and quarterly reflections for professional growth.
• Supportive culture with annual events, company socials, and a volunteering day.