Role: Senior AI/ML Trainer
Location: Bangalore
Employment Type: Full-time
About your Company: Cloud That, founded in 2012 by Bhavesh Goswami, is India’s first company to offer comprehensive cloud consulting and training. Headquartered in Bengaluru with global offices, it has delivered 350+ projects and trained 850K+ professionals across 30+ countries.
A top-tier partner with AWS, Microsoft, Google Cloud, and Databricks, Cloud That is the only company globally to win all three major cloud training awards in 2025. It also holds multiple prestigious partnerships and was certified as a Great Place to Work® in 2025, highlighting its innovation-driven, people-first culture.
About the Role
We are looking for a passionate Senior Technical Trainer with good hands-on to join our expert team. Candidate will drive knowledge adoption across customers, partners, and internal teams delivering high-impact training in AI/ML, Deep Learning, and the rapidly evolving Generative AI & Agentic AI landscape.
Key Responsibilities
- Conduct engaging in-person and virtual training sessions across a range of learner profiles
- Deliver workshops and bootcamps on AI/ML, Deep Learning, Generative AI, RAG pipelines, and Agentic AI systems and LLMOps.
- Design and develop training materials, including slide decks, hands-on labs, demo notebooks, video walkthroughs, and assessments aligned towards current industry trends and customer needs.
- Build modular, reusable learning content covering GenAI application development, RAG architectures, LLM fine-tuning, prompt engineering, and multi-agent orchestration, LLMOps.
- Integrate real-world use cases and project-based learning into every module, ensuring practical applicability.
- Work closely with internal and external Subject Matter Experts (SMEs) to draft training proposals and curate content aligned with enterprise skilling goals.
- Train and mentor internal trainers and partner faculty to scale delivery across regions and formats.
Requirements (Must- have):
- ML and Deep learning frameworks: Scikit Learn, TensorFlow, PyTorch, Keras
- Neural network architectures: CNNs, RNNs, LSTMs, Transformers
- ML workflows: data preprocessing, model training, evaluation, and optimization
- Working knowledge of Large Language Models (LLMs): GPT, Llama, Mistral, Gemini, Claude, etc.
- Prompt Engineering: zero-shot, few-shot, chain-of-thought, and advanced prompting patterns
- RAG (Retrieval-Augmented Generation), Vector databases (Pinecone, FAISS, Chroma, Weaviate), embedding models, chunking strategies
- LLM Fine-tuning: LoRA, QLoRA, PEFT, RLHF
Agentic AI & Frameworks:
- Building and teaching AI Agents — tool use, memory, planning, and reasoning loops
- Hands-on familiarity with at least two or more Agentic AI frameworks: LangChain/LangGraph, LlamaIndex, CrewAI, AutoGen (Microsoft), OpenAI Agents SDK or Anthropic Claude SDK
- Hands-on knowledge of MCP (Model Context Protocol), tool calling, and function calling patterns
- Hands-on knowledge of Multi-Agent system design and its nuances and LLMOps
Qualifications
- Bachelor's degree in computer science, Engineering, Mathematics, or a related field or equivalent practical experience
- Demonstrated hands-on experience in AI/ML model development, GenAI application building, or data science workflows
- Proven track record of delivering technical training, workshops, or bootcamps especially in AI/ML or GenAI domains
- Experience with cloud-based AI/ML platforms (AWS Sagemaker, Azure AI Foundry, GCP Vertex AI, etc.) is highly recommended.
- Having any of professional cloud certifications is a plus
- Prior experience developing content for professional certifications or enterprise skilling programs is a plus
- Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse audiences
- Strong facilitation skills - comfortable engaging beginners as well as seasoned engineers in the same session
- Strong analytical and problem-solving skills with an eye for real-world applicability
Good to have:
- Contributions to open-source AI/ML projects or public learning resources (blogs, notebooks, talks)
- Experience with AI governance, responsible AI practices, or bias/safety considerations in LLMs
- Active community presence (LinkedIn, Hugging Face, GitHub, etc.)
What We Offer:
- Competitive salary and performance bonuses.
- Learning & development opportunities.
- Collaborative and diverse team environment.
- Be a part of the ONLY company in the world to be recognized by Microsoft, AWS, and Google Cloud with prestigious awards in 2025.
Application Process: Shortlisted candidates will be contacted for a Virtual/Face to Face interview. Our process includes a [5–rounds of interview].
Equal Opportunity Statement: We are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, gender, sexual orientation, age, or disability status.
