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Ema

AI Engineer Intern

InternshipHybridBengaluru, Karnataka2 months29K/mo4 openingsImmediate / Rolling

About this internship

Join Ema in Bengaluru as an AI Engineer Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on applied AI engineering work. About the role As an AI Engineer Intern at Ema, your core focus will be building…

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Skills you'll use

PythonLLM APIsPrompt EngineeringRAG PipelinesPyTorch / TensorFlowVector DatabasesModel EvaluationREST APIsData PreprocessingMLOps Basics

What you'll do

  • Work on building AI features into a live product alongside the core team
  • Apply Python, LLM APIs, Prompt Engineering, RAG Pipelines 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, LLM APIs, Prompt Engineering (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 Bengaluru, Karnataka

Perks & benefits

Mentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hours

Interview & selection process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Practical assignment or case study with a short walkthrough

About Ema

Ema operates in the enterprise ai sector and has an active presence in Bengaluru. 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…
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