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IBM logo — IBM AI/ML Engineering Intern at IBM
IBM

AI/ML Engineering Intern

InternshipIn OfficeDelhi, Delhi6 months31K/mo4 openingsImmediate / Rolling

About this internship

IBM has an open AI/ML Engineering Intern position in Delhi for motivated freshers and final-year students. You will work on live AI engineering projects and finish with something you can genuinely talk about in interviews. About the role As a AI/ML Engineering Intern at IBM, your core focus will…

Skills you'll use

PythonFastAPIREST APIsLLM IntegrationDockerModel DeploymentCloud PlatformsGitPrompt EngineeringTesting

What you'll do

  • Work on wiring models into user-facing features, APIs and pipelines alongside the core team
  • Apply Python, FastAPI, REST APIs, LLM Integration 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/BCA/MCA/M.Sc (CS, AI) — 2026 freshers & final-year students welcome
  • Working knowledge of Python, FastAPI, REST APIs (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 Delhi, Delhi

Perks & benefits

Live project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionals

Interview & selection process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Team-fit / behavioural interview with the team

About IBM

IBM operates in the technology sector and has an active presence in Delhi. 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 work runs at…
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