AI & ML Internship

AI/ML Internship Job Description (4-Month Training)

Position: AI/ML Intern
Duration: 4 Months (Full-time)
Type: Internship with Training Certificate & Project Portfolio
Start Date: Immediate (Flexible for Students)

Position Overview

Assist in developing machine learning models, data preprocessing, and AI research projects for real-world applications. Gain hands-on experience with Python, TensorFlow/PyTorch, and deployment workflows while contributing to production-ready AI solutions. Ideal for final-year students or fresh graduates building AI/ML portfolios.​

Key Responsibilities

• Perform data cleaning, feature engineering, and preprocessing using Pandas/Numpy for ML tasks.​
• Train, tune, and evaluate models with Scikit-learn, TensorFlow/Keras, or PyTorch on supervised/unsupervised datasets.​
• Assist in AI model deployment strategies, including Flask/Docker basics and cloud workflows (AWS/Azure intro).​
• Conduct research on AI trends, analyze datasets, and document experiments/findings.​
• Collaborate with engineering teams on model testing, optimization, and technical reports.​
• Build 2-3 portfolio projects (e.g., predictive models, NLP tasks) with mentor guidance.

Required Skills & QualificationsCategoryRequirementsProgrammingPython proficiency; familiarity with Pandas, NumPy, Scikit-learn ​ML KnowledgeUnderstanding of algorithms (regression, classification, clustering); basic deep learning ​Math/StatsLinear algebra, calculus, probability; SQL basics ​ToolsTensorFlow/PyTorch (beginner level), Git; bonus: cloud platforms ​Soft SkillsProblem-solving, communication, teamwork; curiosity for AI research ​EducationPursuing B.Tech/M.Tech CS/Data Science/AI (3rd/4th year preferred) ​

No prior professional experience required; personal projects or coursework suffice.​

Internship Structure & Training

Weekly Breakdown (16 Weeks Total):

• Weeks 1-4: Data handling, ML fundamentals, 1st project (e.g., classification model).
• Weeks 5-8: Deep learning, model optimization, 2nd project (e.g., computer vision).
• Weeks 9-12: Deployment, research, advanced topics (NLP/RL intro).
• Weeks 13-16: Capstone project, presentation, portfolio review.

Benefits:

• Mentorship from industry experts.
• Completion certificate & LinkedIn recommendation.
• Access to datasets, GPU resources, and code repositories.
• Networking with AI professionals.

Application Process

Submit resume, GitHub/portfolio, and 1-page cover letter. Shortlisted candidates complete a 1-hour Python/ML coding test. Interviews focus on problem-solving over experience.

Job Type: Full-time

Pay: ₹273,906.01 - ₹1,433,495.37 per year

Work Location: In person