AI ML Trainer

Edunet Foundation; Haldwani; On-site; INR 600,000 - 900,000; Full time

Job summary

Edunet Foundation seeks experienced educators to deliver AI/ML content and training materials across multiple locations. The role involves instructor-led classroom sessions, webinars, and virtual classrooms for internal and external clients.

You will develop materials covering AI, ML, data analytics, cloud computing, and Gen AI, and keep content updated with the latest industry practices and tools such as LLMs and RAG workflows.

Qualifications

• B.E / B.Tech / M.Tech/ MCA/ Ph.D in Computer Science, IT, Data Science, or equivalent.
• Strong foundation in AI, Machine Learning, Data Analytics, and Python Programming.

Responsibilities

• Delivering course content and materials to internal and external clients through instructor-led classroom presentations, webinars and virtual classrooms.
• Develop and maintain comprehensive training materials that cover fundamental concepts of emerging technologies such as AI-ML, Cloud Computing, Gen AI, Data Analytics, Agentic AI.

Skills

Python programming

Deep Learning

Machine Learning

Data Analytics

Neural Networks

Feature Engineering

LangChain

LLMs

Prompt Engineering

Education

B.E / B.Tech / M.Tech/ MCA/ Ph.D in CS/IT/Data Science

Tools

NumPy

Pandas

Scikit-learn

LangFlow

LangChain

Job description

Education:

• B.E / B.Tech / M.Tech/ MCA/ Ph.D in Computer Science, IT, Data Science, or equivalent.
• Strong foundation in AI, Machine Learning, Data Analytics, and Python Programming.

Multiple Locations:

Haldwani, Ajmer, Kota, Khammam, Warangal, Haveri, Vijayawada, Tirupati

Experience:

Delivering course content and materials to internal and external clients through instructor-led classroom presentations, webinars and virtual classrooms.

Develop and maintain comprehensive training materials that cover fundamental concepts of emerging technologies such as AI-ML, Cloud Computing, Gen AI, Data Analytics, Agentic AI.

Technical Skills:

• Supervised and Unsupervised Learning, Model Training, Testing, and Evaluation
• Feature Engineering and Model Optimization
• Deep Learning fundamentals (Neural Networks, CNN, RNN)
• Python programming, Libraries such as NumPy, Pandas, Scikit-learn
• Working with Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• Designing AI agents and workflows
• Multi-agent systems and orchestration
• Using frameworks such as LangChain, LangFlow, or similar agent frameworks

Location:

• Open to multiple locations as per program requirements.
• Willingness to travel for in-person workshops, faculty training, and student engagements.