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.
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