Generative AI & Machine Learning Trainer

Job Title : Generative AI & Machine Learning Trainer

We are seeking a Generative AI & Machine Learning Trainer with 1–3 years of hands-on experience to design and deliver impactful training programs that transition learners from foundational AI/ML to advanced Generative AI (GenAI) applications. The ideal candidate combines practical GenAI project experience with strong communication and teaching abilities to upskill engineers, analysts, and business teams.

1. Training Program Design & Delivery • Develop and conduct engaging sessions covering: • AI/ML Fundamentals: supervised/unsupervised learning, model evaluation, feature engineering, classical algorithms. • Deep Learning Basics: CNNs, RNNs, Transformers, attention mechanisms. • Generative AI: LLMs, prompt engineering, fine-tuning (LoRA/QLoRA), RAG pipelines, agent workflows, and evaluation metrics.accenture+1 • Create hands-on labs, real-world case studies, and mini-projects aligned with industry use cases (e.g., document QA, code assistants, chatbots). 2. Learner Support & Mentorship • Guide learners through concept clarification, code reviews, and project implementation. • Provide post-training support for query resolution and upskilling guidance. 3. Content & Tooling • Maintain up-to-date training materials reflecting current GenAI frameworks (e.g., LangChain, LlamaIndex, Hugging Face). • Demonstrate deployment of GenAI prototypes on cloud platforms (AWS Bedrock, Azure AI, GCP Vertex AI).accenture • Curate notebooks, datasets, and reference architectures for reproducible learner outcomes. 4. Feedback & Continuous Improvement • Collect learner feedback to refine content depth, pacing, and delivery format. • Recommend new tools, datasets, and pedagogical improvements to enhance learning impact.

& Skills •

: Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field. • Experience: • 1–3 years of professional experience in AI/ML, with demonstrable hands-on work in Generative AI (e.g., LLM apps, RAG, fine-tuning). • Prior experience in training, mentoring, teaching, or technical content creation is strongly preferred. • Technical Proficiency: • Strong command of Python and ML/DL libraries (scikit-learn, TensorFlow or PyTorch). • Practical experience with LLMs, prompt engineering, basic fine-tuning, RAG pipelines, and GenAI evaluation. • Familiarity with vector databases (FAISS, Pinecone, etc.) and cloud AI services is a plus. •