Website Intuit
Intuit India Internship & Co-op Programme 2026
Opportunity Overview
Program Framework & Track Breakdown
[Individual Role Vacancy] ➔ [Application & Portfolio Review] ➔ [Technical & Behavioral Evaluations] ➔ [10-12 Week Bengaluru Onsite/Hybrid Internship]
Core Function Tracks (India Office)
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Software Engineering: Building customer-facing and internal products across frontend (React), backend systems, AI/ML integrations, and Virtual Expert platforms.
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Data Science: Developing models for user preference, time-series forecasting, anomaly detection, trend analysis, and reinforcement learning.
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Product Design: Executing user experience (UX), interaction design, and product flow research.
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Product Management: Defining product discovery, customer problem prioritization, and cross-functional feature execution.
Eligibility Criteria
Baseline Eligibility Rules
Benefits & Relocation Support
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Competitive Stipend: All positions are paid (exact figure disclosed during offer stage).
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Relocation Assistance: Provided to eligible interns enrolled at universities located outside Bengaluru.
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Corporate Perks: Paid volunteering time (8 hours), access to employee resource groups, holiday pay, and recreational campus amenities.
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Industry Exposure: Direct placement on production teams working on core global products (QuickBooks, TurboTax, Credit Karma, Mailchimp).
Application & Selection Process
Step-by-Step Application Steps
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Monitor Channels: Search individual job postings on Intuit Careers, LinkedIn, or Handshake.
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Verify Student Status: Ensure your academic timeline permits returning to university post-internship.
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Tailor Resume: Explicitly align resume projects with the specific vacancy stack (e.g., React, ML pipelines, DSA).
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Talent Community: Option to join Intuit’s Talent Community for automated role alerts.
Technical Preparation Framework
[Data Structures & Algorithms] ➔ [Core Computer Science Fundamentals] ➔ [Resume Project Architecture & Trade-offs] ➔ [Behavioral Alignment]
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Engineering Candidates: Deep-dive into Data Structures, Algorithms, Object-Oriented Design, and production code trade-offs.
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Data Science Candidates: Focus on Python frameworks, statistical modeling, machine learning fundamentals, and SQL.
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Project Review: Be prepared to explain technical challenges, system architecture, personal contribution, and testing strategies for every listed resume project.
To apply for this job please visit remotejobhiring.com.
