Machine Learning Intern

Job description

## About the role Crossing Infotech is offering a Machine Learning Internship for freshers and entry‑level candidates. The role focuses on the end‑to‑end machine‑learning lifecycle, from data preparation and feature selection to model training, evaluation, and documentation. The internship is virtual/remote and lasts 1–3 months with a stipend. ## Responsibilities - Prepare, clean, and preprocess datasets for ML projects. - Conduct exploratory data analysis to uncover patterns. - Use Python libraries (e.g., Pandas, NumPy, Scikit‑learn) to build supervised and unsupervised models. - Split data into training, validation, and test sets; train and evaluate models using appropriate metrics. - Experiment with feature engineering, model parameters, and compare different approaches. - Create visualizations to illustrate data insights and model performance. - Maintain clear documentation of experiments, results, and technical decisions. ## Required qualifications - Basic to intermediate knowledge of Python. - Understanding of fundamental machine‑learning concepts and statistics. - Familiarity with data preprocessing and supervised learning basics. - Analytical mindset, problem‑solving ability, and eagerness to learn. ## Preferred skills - Experience with Scikit‑learn, Pandas, NumPy. - Knowledge of regression, classification, and clustering algorithms. - Ability to use Matplotlib (or similar) for visualizations. - Exposure to feature engineering, evaluation metrics (accuracy, precision, recall, F1‑score, RMSE). - Familiarity with Jupyter Notebook and Git. ## What you will learn - Complete machine‑learning project workflows from start to finish. - Advanced data preprocessing and feature preparation techniques. - Exploratory data analysis for ML projects. - Fundamentals of supervised and unsupervised learning. - Model training, evaluation, and comparison. - Practical experience with ML tools and best practices.

Required skills

Compensation

Estimated range — based on ML/Data Engineer with 0-1 years experience (5 similar listings). Actual compensation may vary based on your specific experience, interview performance, and the company’s internal bands.