AI Engineer Intern

Job Description

Role - AI Engineer Intern

Exp - 6 months - 1year

Location - Mohali, PB

Work Mode - Work from office ( 12-10pm IST)

Position Overview

We are seeking a highly motivated AI Engineer Intern to join our engineering team. This

is an exciting opportunity to work alongside experienced engineers and researchers to

develop, train, and deploy AI models. You'll also explore and implement modern AI tools

to improve workflows and enhance productivity across internal teams.

Key Responsibilities

 Assist in designing, developing, and testing machine learning models.

 Collect, clean, and preprocess datasets for training and evaluation.

 Perform exploratory data analysis (EDA) to extract meaningful insights.

 Implement and optimize algorithms using frameworks such as TensorFlow,

PyTorch, or scikit-learn.

 Collaborate with cross-functional teams to integrate models into production

environments.

 Explore emerging AI tools and platforms (e.g., automation, NLP assistants,

no-code AI, etc.) and evaluate their applicability to internal operations.

 Prototype and implement AI-driven solutions to streamline internal

processes, such as documentation, data analysis, reporting, or workflow

automation.

 Document findings, models, and codebase to ensure reproducibility.

 Stay updated with the latest trends and advancements in AI/ML.

Qualifications

 Currently pursuing a degree in Computer Science, Data Science, Engineering,

Mathematics, or a related field.

 Solid understanding of machine learning concepts and algorithms.

 Proficiency in Python and common ML libraries (e.g., NumPy, pandas, scikit-

learn).

 Experience with deep learning frameworks such as PyTorch or TensorFlow is a

plus.

 Familiarity with NLP, computer vision, or time series analysis is a bonus.

 Strong analytical and problem-solving skills.

 Excellent communication and teamwork abilities.

Preferred Qualifications

 Previous project or internship experience in AI/ML.

 Interest or experience in productivity tools, automation, or process optimization.

 Knowledge of cloud platforms (AWS, GCP, or Azure).

 Experience with version control (e.g., Git) and collaborative development.