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Airbus

Aerolens Intern - Integration Test & Analysis

About this role

This roughly 6-month internship is in the Integration Test & Analysis department at Airbus India in Bengaluru, ideally starting in January 2027 (flexible). It centres on AeroLens, a tool for health engineers working with flight telemetry data and technical documentation. The intern helps build the data architecture, an AI-powered RAG core with hybrid search and re-ranking, and an interactive UI for querying parameters and running diagnostics. A tutor supports the intern's development. It suits students in computer science, electronics or aerospace who know Python and LLMs.

Airbus is hiring for Aerolens Intern - Integration Test & Analysis, an internship based in Bengaluru.

Who can apply: Student. Duration: 6 months. Skills: Python, LLMs, RAG, Vector databases, Hybrid search.

Hirastra checked that this opening is live. Apply directly through the official posting; applying is always free.

What you'll do

  • Design and implement an end-to-end telemetry and engineering data architecture for flight datasets and technical documents
  • Develop a RAG and intelligence core with query expansion, hybrid search and semantic re-ranking
  • Build the AeroLens interactive UI for querying parameters, visual diagnostics and failure impact analysis

What you need

  • Currently pursuing a Bachelor's or Master's in Computer Science, Electronics & Communication, Aerospace Engineering or a related technical field
  • Proficiency in Python
  • Familiarity with LLMs and RAG architectures
  • Basic understanding of or strong interest in handling unstructured engineering documentation
  • Team spirit, strong communication and a proactive, autonomous attitude
  • Fluent English
  • Nice to have: knowledge of aircraft systems
Location
Bengaluru
Work mode
See listing
Experience
Student
Duration
6 months
Pay
₹25K–40K/mo (Est.)
Type
Internship, AI & ML
Added
13 October 2026

Skills

  • Python
  • LLMs
  • RAG
  • Vector databases
  • Hybrid search

"Est." = Hirastra's estimate based on market data, not an official figure.

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