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
Num Py
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
Tensor Flow
Keras
Artificial Neural Networks (ANN)
CNN
RNN
LSTM
Transfer Learning
NLP & Time Series
Text Pre-processing
TF-IDF
Word2

Vec
Named Entity Recognition (spaCy)
Sentiment Analysis
Topic Modelling
ARIMA / SARIMA
FB Prophet
Deployment & MLOps
FastAPI
Streamlit
Docker
MLflow
AWS EC2 / Render
Git & Git Hub
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.