Kantar
AI / Machine Learning Intern
InternshipWork from HomeNoida, Uttar Pradesh3 months28K/mo3 openingsImmediate / Rolling
About this internship
Start your career in applied AI and machine learning with Kantar as an AI / Machine Learning Intern in Noida. You will sit with a working team, use the same tools and systems they do, and own a defined piece of work from day one.
About the role
As an AI / Machine Learning Intern at Kantar, your…
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Skills you'll use
PythonMachine LearningDeep LearningPyTorch / TensorFlowScikit-learnPandasFeature EngineeringModel EvaluationSQLMLOps Basics
What you'll do
- Work on training, evaluating and deploying models alongside the core team
- Apply Python, Machine Learning, Deep Learning, PyTorch / TensorFlow to live, production-facing problems
- Document your work clearly for reviewers and stakeholders
- Participate in reviews and act on the feedback you receive
- Collaborate across engineering, product, design or business as required
- Follow the team's quality, testing and documentation standards
Who can apply
- Pursuing or recently completed B.E./B.Tech/M.Tech/MCA/M.Sc (CS, Statistics, Maths) — 2026 freshers & final-year students welcome
- Working knowledge of Python, Machine Learning, Deep Learning (or a genuine willingness to learn them)
- Strong fundamentals in your discipline and clear problem-solving ability
- Care with detail and the discipline to document your work
- Clear written and verbal communication in English
- Based in or willing to work from Noida, Uttar Pradesh
Perks & benefits
Letter of RecommendationMentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunity
Interview & selection process
2 rounds — typical selection flow for this role:
- 1Application screening & resume shortlisting by the talent team
- 2Technical interview on fundamentals and your projects
About Kantar
Kantar operates in the market research & analytics sector and has an active presence in Noida. Interns here are put on real work from the start, because the team's view is that the fastest way to learn a craft is to practise it under people who already do it well — not to watch it from a…
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