Generative AI Intern at Tiger Analytics

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Skills you'll use

What you'll do

• Build and evaluate LLM-powered features and prototypes.
• Design retrieval pipelines over internal document sets.
• Measure output quality against defined evaluation criteria.
• Document prompt and model behaviour, including failure modes.
• Document your work so the next person can pick it up

Who can apply

• Education: pursuing or completed B.E./B.Tech/BCA/MCA/B.Sc in CS, IT or a related discipline
• Graduation year: 2025, 2026 or 2027 batch
• Minimum 60% / 6.0 CGPA (relaxable for candidates with strong practical projects)
• Technical skills: working knowledge of Python, Large Language Models, Prompt Engineering, RAG
• Soft skills: clear written communication, ownership, willingness to document work
• Experience: none required — freshers welcome; prior projects or certifications are a plus

Perks & benefits

Interview & selection process

1. 1The selection process for the Generative AI Intern role at Tiger Analytics is merit-based and typically runs over 4 stages: Round 1: Application & Resume Screening — apply through this page; profiles are shortlisted on fundamentals, projects and role fit. Round 2: Online Assessment — aptitude plus role-specific questions covering Python, Large Language Models, Prompt Engineering. Round 3: Technical / Functional Interview — a discussion of your projects and practical scenarios covering Python, Large Language Models, Prompt Engineering, RAG, LangChain. Expect "how would you approach this?" rather than definitions. Round 4: HR Discussion — role expectations, stipend, start date, location and offer. Shortlisted candidates are contacted after applying. There are no charges at any stage of the process — Tiger Analytics never asks candidates for money.

About Tiger Analytics

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