AI/ML Trainer

3. Job Description – AI/ML Trainer

About the Role

We are looking for an experienced AI/ML Trainer to deliver instructor-led classroom training to engineering students. The trainer will be responsible for delivering technical sessions, conducting hands-on labs, mentoring students on mini projects and capstone projects,and ensuring students gain practical, industry-relevant skills.

Key Responsibilities

• Deliver engaging classroom training on Data Science, Machine Learning, and Deep Learning concepts to engineering students.
• Conduct instructor-led sessions covering theory, coding demonstrations, hands-on labs, assignments, and project mentoring.
• Deliver training aligned with the prescribed curriculum, including:
• Python for Data Science
• Statistics & Probability for Machine Learning
• Supervised Learning
• Unsupervised Learning & Feature Engineering
• Deep Learning & Neural Networks
• Natural Language Processing (NLP) & Time Series Analysis
• ML Model Deployment using FastAPI, Streamlit, Docker, and AWS
• Conduct practical sessions using industry-standard datasets and real-world use cases.
• Mentor students in completing mini projects and capstone projects.
• Evaluate students through assessments, coding exercises, assignments, and project reviews.
• Collaborate with the academic team to ensure timely completion of the training schedule and maintain high training quality.

Technical Skills Required

The candidate should have hands-on expertise in:

Programming & Data Analysis

• Python
• NumPy
• Pandas
• Matplotlib
• Seaborn
• Jupyter Notebook / Google Colab

Machine Learning

• Regression & Classification
• Decision Trees
• Random Forest
• Support Vector Machines (SVM)
• K-Nearest Neighbours (KNN)
• XGBoost / LightGBM
• Model Evaluation
• Cross Validation
• Hyperparameter Tuning
• Feature Engineering

Deep Learning

• TensorFlow
• Keras
• Artificial Neural Networks (ANN)
• CNN
• RNN
• LSTM
• Transfer Learning

NLP & Time Series

• Text Pre-processing
• TF-IDF
• Word2Vec
• Named Entity Recognition (spaCy)
• Sentiment Analysis
• Topic Modelling
• ARIMA / SARIMA
• FB Prophet

Deployment & MLOps

• FastAPI
• Streamlit
• Docker
• MLflow
• AWS EC2 / Render
• Git & GitHub

Eligibility

• Bachelor‘s or Master‘s degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related discipline.
• Minimum 3–5 years of industry experience in AI/ML development and/or technical training.
• Prior experience in delivering classroom training to engineering students is highly preferred.
• Strong practical knowledge of Python, Machine Learning, Deep Learning, NLP, and ML deployment.
• Excellent communication, presentation, mentoring, and classroom management skills.