Job Description

AI/ML Internship (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 & QualificationsCategoryRequirements

Programming

Python proficiency; familiarity with Pandas, NumPy, Scikit-learn ?

ML Knowledge

Understanding of algorithms (regression, classification, clustering); basic deep learning ?

Math/Stats

Linear algebra, calculus, probability; SQL basics ?

Tools

TensorFlow/PyTorch (beginner level), Git; bonus: cloud platforms ?

Soft Skills

Problem-solving, communication, teamwork; curiosity for AI research ?

Education

Pursuing 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