AI/ML Trainer

AS Technology Corporation; Delhi; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

AS Technology Corporation in Delhi seeks an experienced AI/ML Trainer to deliver instructor-led classroom training to engineering students. The trainer will mentor students on mini and capstone projects and ensure practical, industry-relevant skills.

Responsibilities include hands-on labs, labs, assessments, and collaboration with the academic team to maintain high training quality. Strong Python and ML deployment skills are required.

Qualifications

• Hands-on expertise in data science and ML across Python ecosystems.
• 3–5 years of industry experience in AI/ML development or training.
• Experience delivering classroom training to engineering students is preferred.
• Strong communication, presentation, mentoring and classroom management.

Responsibilities

• Deliver engaging classroom training on Data Science, Machine Learning and Deep Learning concepts.
• 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 ML; Supervised Learning; NLP & Time Series.
• ML Deployment topics: FastAPI, Docker and AWS; practical sessions with real datasets.
• 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.

Skills

Python

NumPy

Matplotlib

Seaborn

Jupyter Notebook/Colab

Regression & Classification

Decision Trees

XGBoost/LightGBM

Cross Validation

Hyperparameter Tuning

TensorFlow

CNN

RNN

LSTM

NLP basics

Education

Bachelor's or Master's in Computer Science, Artificial Intelligence, Data Science, IT

Tools

FastAPI

Docker

MLflow

Git & GitHub

Job description

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‑ons 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
• 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
• Matplotlib
• Seaborn
• Jupyter Notebook / Google Colab
• Regression & Classification
• Decision Trees
• XGBoost / LightGBM
• Cross Validation
• Hyperparameter Tuning
• TensorFlow
• CNN
• RNN
• LSTM

NLP & Time Series

• Text Pre‑processing
• TF‑IDF
• Word2Vec
• Named Entity Recognition (spaCy)
• Sentiment Analysis
• ARIMA / SARIMA

Deployment & MLOps

• FastAPI
• Docker
• MLflow
• Git & GitHub
• 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.