Tech Data Automation Specialist - Knowledge Systems & Machine Learning
Airbus India Private Limited
India
Hybrid
Knowledge graph development with typedb or neo4j
Machine learning pipeline architecture and deployment
Generative ai and large language model integration
Airbus India Private Limited is seeking a Tech Data Automation Specialist to join their Technical Data Support & Services team. This hybrid role focuses on developing knowledge systems and machine learning pipelines to enhance aircraft maintenance documentation and support efficient operations
Job Summary
The role focuses on developing advanced logical databases and knowledge graph systems to support safe aircraft operations.
Candidates will build end-to-end AI and Generative AI pipelines integrating LLMs and Retrieval-Augmented Generation techniques.
This position is part of Airbus Customer Services Ambition 2030 aimed at bringing significant efficiency through process automation.
Matching Summary
Match Score: 85
Airbus India Private Limited is seeking a Tech Data Automation Specialist to join their Technical Data Support & Services team. This hybrid role focuses on developing knowledge systems and machine learning pipelines to enhance aircraft maintenance documentation and support efficient operations.
Skills & Requirements
Must-have
Knowledge graph development with TypeDB or Neo4j
Machine learning pipeline architecture and deployment
Generative AI and Large Language Model integration
Python programming for data engineering tasks
Full-stack development including GUI frontends
Nice-to-have
Experience in aerospace digital transformation
Familiarity with Hierarchical Task Networks (HTN)
MLOps tools like MLflow or Kubeflow
Lean tools and Value Stream Mapping methodology
Strong communication skills in technical English
Key Requirements
Bachelor's or Master's degree in Computer Science Engineering
4-8 years of professional experience in software or data roles
Proficiency in knowledge representation principles
Hands-on experience with Scikit-learn, TensorFlow, or PyTorch