Senior AI/ML Trainer

• *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.)

Pay: ₹665,000\.00 \- ₹1,940,000\.00 per year

Benefits

• Flexible schedule

Work Location: In person