Role overview
Data & AI Trainer
Location:** Home Based with required travel to QA centres and client sites
Your Role:
As an expert in your field, you will deliver QA and vendor specific innovative, high-quality training in Data Science, GenAI, and Python to a wide range of clients. You will empower learners to apply their knowledge effectively in real-world scenarios. You’ll maintain high satisfaction scores, contribute as a subject matter expert, and collaborate across teams to support shared goals and continuous improvement.
In addition to training delivery, you’ll play a key role in shaping the future of learning by contributing insights to the design and development of cutting-edge courses. With strong technical expertise in GenAI, machine learning, Python, and the NumPy ecosystem, and desirable experience in AI frameworks and cloud platforms, you’ll stay at the forefront of industry trends through ongoing professional development and a passion for education.
Responsibilities
- Training Delivery: Deliver high quality and engaging training in line with polices, industry standards and regulatory requirements.
- Performance & Quality Metrics: Attain a consistent Trainer Satisfaction Score (TSAT) of 92%+ and achieve ‘Meeting Expectations’ in trainer observations, utilise feedback to improve performance and effectiveness of training, conduct peer observations providing constructive feedback.
- Subject Matter Expertise: Act as an SME utilising your in-depth knowledge to contribute insights to internal discussions, client programmes and collaborate cross functionally
- Communication: Collaborate effectively across teams, maintaining professional proactive communication with internal and external stakeholders
- Contribution: Support team objectives and initiatives, demonstrate accountability and reliability showing flexibility to adapt to priorities
- Continuous Professional Development: Proactively maintain industry recognised certifications, engage in continued learning to stay up to date with industry trends, emerging tech and best practices
- Excellent presentation, facilitation, and coaching skills to effectively deliver complex technical content in an engaging and interactive manner virtually and/or in-person
- Ability to connect with diverse audiences including technical and non-technical professionals
- Deep understanding of AI frameworks, concepts, and real-world applications, including strong capability in prompt engineering, LLM optimisation, multimodal AI and emerging agentic AI systems (reasoning, planning, and tool‑using AI agents)
- Hands on experience applying machine learning techniques, statistical modelling, and generative AI methods to solve complex business problems
- Advanced proficiency in Python (including NumPy, Pandas, Scikit-learn), with experience building, training, and deploying ML models.
- Strong technical capability in key data science and AI languages and frameworks such as R, PyTorch, TensorFlow, Java, LangGraph and modern model development toolkits
- Experience designing or working with scalable data architectures and distributed data processing frameworks such as Apache Spark or Databricks
- Familiarity with MLOps practices and tools is advantageous.
- Working familiarity with modern cloud ecosystems (AWS, Azure, GCP) including AI/ML services, data lake architectures, and cloud native tooling
- Experience collaborating with AI/ML engineers, data scientists, software developers, and cross-functional technical team
- Awareness of data governance, ethics, compliance, and frameworks for responsible AI use
- Desirable experience contributing to or managing AI development projects aligned to business strategy and regulatory considerations
- Strong knowledge of GenAI concepts, applications and prompt engineering
- Proficient in GenAI concepts, machine learning techniques, and Python programming, with strong familiarity with the NumPy ecosystem.
- Desirable hands-on experience with leading AI frameworks (e.g. TensorFlow, PyTorch)
- Familiarity with cloud platforms (AWS, GCP, Azure)
- Experience working with AI/ML engineers, data scientists, and other data professionals
- Passion for education, technology, and empowering others through knowledge sharing
- Desirable degree in Mathematics or related field
- Desirable MSc/PhD in Data Science, AI, Computer Science, or relevant certifications
- Desirable relevant cloud vendor (GCP, AWS, Azure) certifications
- Desirable NVIDIA Deep Learning institute Certifications
About the company
- 27 days Annual Leave (4 days used for the festive closure) plus Bank Holidays
- Holiday Buying scheme
- Medicash plan, Wellhub, Cycle to Work scheme
- Private Medical Insurance at corporate rates
- Employee Assistance Programme
- Employee Discounts Benefit Hub
- 3 Development days
- 2 Charity days per year
- Pension Scheme
- Early Friday Finish at 4pm
Tags & focus areas
Used for matching and alerts on DevFound Ai Machine Learning Data Science