IQVIA

Machine Learning Intern

InternshipIn OfficeIndore, Madhya Pradesh2 months27K/mo1 openingImmediate / Rolling

About this internship

IQVIA is hiring a Machine Learning Intern in Indore — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to applied machine learning rather than a certificate-only programme. About the role As a Machine Learning Intern at IQVIA, your core focus will be…

Skills you'll use

PythonMachine LearningScikit-learnTensorFlowPyTorchFeature EngineeringModel EvaluationPandasNumPyMLOps Basics

What you'll do

Work on training, tuning and validating ML models on production data alongside the core team
Apply Python, Machine Learning, Scikit-learn, 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/M.Sc (CS, Statistics, Maths) — 2026 freshers & final-year students welcome
Working knowledge of Python, Machine Learning, Scikit-learn (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 Indore, Madhya Pradesh

Perks & benefits

Internship CertificateLetter of RecommendationMentorship from a named mentorLive project experienceExposure to professional tools and workflows

Interview & selection process

3 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Team-fit / behavioural interview with the team
3HR discussion — stipend, start date, expectations and offer

About IQVIA

IQVIA operates in the healthcare analytics sector and has an active presence in Indore. 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 distance. The…

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