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Yellow.ai

Machine Learning Intern

InternshipIn OfficeIndore, Madhya Pradesh3 months29K/mo3 openingsImmediate / Rolling

About this internship

Start your career in applied machine learning with Yellow.ai as a Machine Learning Intern in Indore. 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 a Machine Learning Intern at Yellow.ai, your core focus…

Skills you'll use

PythonMachine LearningScikit-learnTensorFlowPyTorchFeature EngineeringModel EvaluationPandasNumPyMLOps Basics

What you'll do

  • Work on training, tuning and validating ML models on real 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

Pre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsInternship CertificateLetter of Recommendation

Interview & selection process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Online aptitude / domain assessment

About Yellow.ai

Yellow.ai operates in the artificial intelligence 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…
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