Data Engineer - Embedded AI (f/m/d), Toulouse

Airbus Group - Airbus Defence & Space

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Data Engineer - Embedded AI (f/m/d), Toulouse

CDI
Aéronautique
IT / Informatique
Publiée depuis 1 jour
 

Airbus Group - Airbus Defence & Space

Airbus is a leading aircraft manufacturer with the most modern and comprehensive family of airliners on the market, ranging in capacity from 100 to more than 500 seats. Airbus champions innovative technologies and offers some of the world’s most fuel efficient and quiet aircraft. Airbus has sold over 13.800 aircraft to more than 360 customers worldwide. Airbus has achieved more than 8,000 deliveries since the first Airbus aircraft entered into service. Headquartered in Toulouse, France.

Tasks

  • Manage data flows to support the training and validation of new machine learning functions (e.g., vision-based navigation or obstacle detection).
  • Design and maintain scalable data pipelines and architectures for machine learning functions, ensuring certification compliance (EASA).
  • Support the Work Package Leader in subcontracting activities
  • Align and communicate with internal stakeholders (R&T, System Engineering, IT)
  • Foster Data Engineering best practices (DataOps, CI/CD) across the project and system engineering community.

Profile

  • Master’s degree in Computer Science, Data Engineering, Software Engineering, or equivalent.
  • Minimum of 5 years experience in Data Engineering and Data Architecture in industrial environments (image processing / computer vision application pipelines highly desirable).
  • Technical Expertise:
  • Architecture & Pipelines: Design and maintain scalable data lakes, optimized data models (Star/Snowflake) and ETL/ELT pipelines within cloud environments (AWS, BigQuery, Mongo), with a specific focus on image processing, tagging, and labeling.
  • Operational Excellence: Implement CI/CD automation, enforce data governance and quality standards, and continuously tune systems for performance and cost efficiency.
  • Collaboration: Partner with cross-functional teams to integrate MLOps practices and facilitate the deployment of AI models.
  • Technical Implementation: Strong proficiency in SQL and NoSQL. Experience with Spark/PySpark, Airflow, Docker/Kubernetes, and MLOps is highly desirable.
  • Languages: Negotiation level in English; knowledge of German or French would be a plus.

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