GenAI Intern (India Innovation Team)

Airbus; Bengaluru; On-site; INR 180,000 - 260,000; Full time

Job summary

Airbus Bengaluru is seeking a hands-on AI engineer to advance RAG and LLM deployment across internal tools. You will work on end-to-end generative AI workflows from data handling through model deployment.

You will prototype and fine-tune small transformer models, prepare data, and contribute to LLM orchestration frameworks, with production deployment and monitoring.

Qualifications

• Experience researching and implementing RAG and advanced LLM techniques for innovation initiatives.
• Data preparation, quantization, and fine-tuning pipelines for deployment.
• Train small transformer models and contribute to internal LLM orchestration frameworks.

Responsibilities

• End-to-end generative AI workflows from data handling through model deployment.
• Hands-on experimentation with state-of-the-art language model architectures and methods.
• Integration of LLMs into Airbus's internal tools and systems.

Skills

Python

Data wrangling

LangChain

LlamaIndex

VectorDB

Transformer architectures

Tokenizer

PyTorch

TensorFlow

Git

Job description

Batch: 2026/2027/2028.

About the role:

• Research and put into practice RAG and advanced LLM techniques in support of Airbus innovation initiatives
• Work on data preparation, quantization, and fine-tuning pipelines to ready models for deployment
• Help train small transformer models and contribute to building internal LLM orchestration frameworks
• Deploy trained models to production environments and monitor their performance

What you’ll work on:

• End-to-end generative AI workflows from data handling through model deployment
• Hands-on experimentation with state-of-the-art language model architectures and methods
• Integration of LLMs into Airbus's internal tools and systems

What we’re looking for:

• Strong Python programming abilities
• Demonstrated experience preparing and wrangling data for machine learning
• Working knowledge of LangChain, LlamaIndex, and VectorDB
• Understanding of transformer architectures and tokenizer behavior
• Proficiency with PyTorch or TensorFlow
• Familiarity with Git for version control