Role Overview

We are seeking a skilled instructor with strong hands-on expertise in Python and Machine Learning who can deliver live, interactive, and outcome-oriented learning sessions. The candidate should be able to simplify complex and math-heavy ML concepts, use practical datasets and visualizations, and help students independently build and interpret machine learning models.

Prior teaching or edtech experience is preferred. However, candidates with strong real-world or academic ML project experience and excellent communication skills may also be considered.

Key Responsibilities

- Deliver live interactive sessions on Python, from beginner to advanced levels.
- Teach Machine Learning fundamentals with a strong focus on conceptual clarity and practical implementation.
- Cover core Python and ML libraries, including NumPy, Pandas, Matplotlib, Seaborn, and Scikit-learn.
- Teach supervised and unsupervised learning concepts.
- Cover regression, classification, clustering, feature selection, data preprocessing, and model evaluation.
- Explain algorithms through real-world examples, practical datasets, visualizations, and hands-on coding exercises.
- Guide students through end-to-end ML project development, including data cleaning, preprocessing, model development, evaluation, optimization, and interpretation of results.




- Help students understand why an algorithm works and when a particular model should be used, rather than focusing only on library-based implementation.
- Address student doubts effectively and ensure high learner engagement and participation.
- Assess student progress and support students in becoming capable of building machine learning models independently.

Required Skills

- Strong expertise in Python is mandatory.
- Strong understanding of Machine Learning fundamentals is mandatory.
- Hands-on experience with NumPy, Pandas, Scikit-learn, Matplotlib, and Seaborn.
- Good understanding of supervised and unsupervised learning techniques.
- Strong knowledge of regression, classification, clustering, data preprocessing, and feature selection.
- Good knowledge of model evaluation metrics, including accuracy, precision, recall, F1-score, and related concepts.
- Transparent understanding of overfitting, underfitting, bias-variance trade-offs, and model improvement techniques.
- Ability to simplify complex technical and mathematical concepts for students.
- Excellent communication and presentation skills in English; proficiency in Hinglish will be preferred.
- Ability to conduct structured, interactive, and practical classroom sessions

📌 Python & AL ML Instructor (Gurugram)
🏢 Sunstone Education
📍 Gurugram