AI Engineer Intern

About the Role

We are looking for an AI Engineer Intern to join our engineering team in Pune. This is a hands-on internship for someone in their final year of study or newly graduated, who wants real experience building machine learning features for client products rather than working from a syllabus. You will be paired with a senior engineer, given a real piece of a real project, and expected to ship it — with support, not by yourself. Strong performers are offered a full-time role at the end of the internship.

Key Responsibilities

• Build and evaluate machine learning models under the guidance of a senior engineer
• Prepare, clean, and explore datasets used for model training and evaluation
• Write Python code for data pipelines, training scripts, and model evaluation
• Help integrate trained models into backend services and APIs
• Document experiments clearly enough that a mentor can review results without a meeting
• Read and summarise relevant papers or documentation when a project calls for a technique the team has not used before
• Write unit tests for the code you contribute
• Participate in code review as both a reviewer and a reviewee
• Present your work at the end of the internship to the engineering team

Requirements

• Currently pursuing or recently completed a degree in Computer Science, Data Science, or a related field
• Working knowledge of Python and basic data structures
• Coursework or personal projects involving machine learning, e.g. classification, regression, or a Kaggle competition
• Familiarity with a machine learning library such as scikit-learn, TensorFlow, or PyTorch
• Comfortable with basic statistics and linear algebra as they apply to ML
• Curiosity and the ability to say “I do not know yet, but here is how I would find out”
• Available for a full-time internship based in Pune

What We Offer

• A stipend benchmarked to market rates for AI internships in Pune
• A defined path to a full-time offer for interns who perform well
• Direct mentoring from senior AI engineers on real client work
• Hybrid working with flexible hours around core collaboration time
• Access to compute resources and paid courses relevant to your project
• A small team where your contributions are visible and credited