System Engineer - Artificial Intelligence (d/f/m)

Key Skills

Java Programming, Python Programming, SQL, DXP solutions, Machine learning techniques, Data Analytics, Algorithms, MLOps tools, Information Intelligence

Job Description

The Airbus Cabin & Cargo Systems team is a great environment for people who want to do their best at work, learn and grow in a professional environment. We are responsible for the Airbus aircraft engineering cabin & cargo systems which are the direct interface to the cabin crew and passengers. We develop, design and support the final product in service.

Your benefits

• Attractive salary including holiday pay, Christmas bonus and profit sharing
• 30 days of vacation and extra days-off for special occasions
• Communities of Practice and specific Career paths for those passionate to become Experts, Architects, Project Managers, Senior Developers, Digital Makers, etc..
• Learning & development opportunities through our Airbus academies (e.g. Digital Academy, Programme & Project Management Academy, etc), Communities of Practice, Airbus Leadership University and our ever-enriching catalogue of online and face-to-face courses
• Special benefits: employer-funded pension, employee stock options, discounted car leasing, special conditions for insurances, public transport subsidy, discounts at local businesses
• On-site-facilities: Company kindergarten, medical officer for check-ups and other health-related services, canteen and cafeteria

You will have the opportunity to organize, lead and drive the AI ecosystem for key strategic projects, grow together with the Airbus AI network and learn about aircraft systems engineering. You will be involved in engineering key projects and you will have the responsibility to define and develop AI functions. This includes the definition of AI applications on product level, specification, design and coding of the embedded software (on demonstrator level). You will be working autonomously and are responsible for the definition and execution of your projects.

Your tasks and responsibilities

• Evaluation, validation, development and implementation of AI functions in the field of aircraft cabin and cargo systems (e.g. monitoring system, fire protection, lights, passenger information system, cargo loading)
• Creation of novel aircraft applications and proof of concepts by combining various data sources (ie. data fusion), including images, video footage, sensor data etc. using data analytics and machine learning methods
• Creation and operation of Machine Learning / AI empowered systems eg. MLOps including software & hardware
• Data acquisition, data cleaning, model creation, validation and deployment for inference and selection of appropriate metrics, algorithms for backend and frontend
• Definition, evaluation and validation of hardware for model creation, deployment and operations including embedded systems
• Close collaboration with experts from engineering and technology development as well as with external project partners, interfacing with data analysts and AI network
• Market monitoring with focus on trends, technologies, solutions, partners and customer needs

Desired skills and qualifications

• Degree in Electrical Engineering, Computer Science, Information Technology, Telecommunication or similar
• Mainly you bring a strong AI competence in an engineering environment
• As a plus: demonstrated experience with AI / machine learning applications with focus on video / image processing, experience with robotics, audio processing or Reinforced Learning 
• Solid proficiency in AI programming languages and packages/libraries (eg. python), hardware (embedded and microcontroller level), software definition for local (edge) and cloud based solutions, deep learning methods and neural networks
• Ability to communicate the subject of AI to non-specialists and to promote the technology in order to influence and convince affected people and stakeholders
• Self-organized and autonomous working method, open-minded and curious, good networker
• Ready to travel partly (mainly Hamburg & Buxtehude, less frequently to Toulouse)