Machine Learning Engineer Internship

About the Opportunity

The role of a Machine Learning Engineer Intern is an excellent opportunity for students passionate about AI and intelligent systems. This internship is specially designed for freshers and college students who are eager to apply their academic learning in a practical environment. As an ML Engineer Intern, you will work on real-world problems involving large datasets, build predictive models, and learn how to deploy them in real systems. This internship provides deep exposure to data pipelines, ML algorithms, and model production, preparing students for a successful career in artificial intelligence.

Responsibilities of the Candidate

• Assist in the collection, cleaning, and preprocessing of data for ML tasks.
• Design and implement ML models using libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Optimize model performance using hyperparameter tuning techniques.
• Collaborate with data scientists and software engineers to integrate models into applications.
• Perform exploratory data analysis (EDA) and visualize key patterns.
• Contribute to the automation of model training and evaluation workflows.
• Document model development steps and maintain version control using Git.

Requirements

• Currently pursuing a degree in Computer Science, Data Science, or related field.
• Strong understanding of Python programming and ML libraries (Scikit-learn, TensorFlow, NumPy).
• Familiarity with basic machine learning concepts (regression, classification, clustering).
• Good knowledge of statistics, probability, and linear algebra.
• Understanding of data structures and algorithms.
• Curiosity to explore real-world data problems and a mindset for continuous learning.
• Prior mini-projects or Kaggle experience will be considered a plus.