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🤖ML Engineer

Master student (d/f/m) in the field of onboard AI/ML for 5G/6G Satellite Non-Terrestrial Networks

AG · München Area
// classified as
ML Engineer (Productionizing models, serving, MLOps.)
posted
1d ago
location
München Area
languages
python
tools
—
> stack
pythonpytorch
> education
master
> description

Job Description:

In order to support the Digital Payload Processors Design Team, Airbus Defence and Space is looking for a

Master student  (d/f/m)  in the field of onboard AI/ML for 5G/6G Satellite Non-Terrestrial Networks

You are a full-time student (d/f/m), looking for a master thesis and want to get to know the work of a AI engineer for space systems?We look forward to you supporting us in the Digital Payload Processors as a Master student (d/f/m)!

  • Location: Taufkirchen/Ottobrunn, near Munich

  • Start: 01.10.2026

  • Duration: 6 months

Your location

Our site is just a stone's throw away from Munich, the beautiful capital of Bavaria. Are you into sports and other outdoor activities? The Alps and Lake Starnberg are within an hour’s reach, offering a multitude of recreational options.

Your benefits

  • Attractive salary and work-life balance with an 35-hour week (flexitime).

  • Mobile working after agreement with the department.

  • International environment with the opportunity to network globally.

  • Work with modern/diversified technologies.

  • At Airbus, we see you as a valuable team member and you are not hired to brew coffee, instead you are in close contact with the interfaces and are part of our weekly team meetings.

  • Opportunity to participate in the Generation Airbus Community to expand your own network.

Your tasks and responsibilities

Your core mission is to answer a critical scientific question: How do hybrid CNN/LSTM models perform on space-grade hardware under strict resource constraints of next-generation satellite communications?

Your tasks will focus on deploying AI models on our next-generation FPGA-based System-on-Chip (SoC) spacecraft processor system. This includes:

  • Analyzing and partitioning the AI model to divide workloads between standard neural processors and custom hardware domains.

  • Exploring the deployment of hybrid CNN/LSTM models on hardware architectures.

  • Optimizing and quantizing the network to drastically reduce memory overhead and power consumption for space deployment.

  • Profiling system performance by measuring real-time execution latency, throughput, and power efficiency under space-grade constraints.

  • Validating model accuracy to ensure the hardware deployment meets strict 5G/6G communication standards.

  • Potential scope includes exploring the development of high-performance C/C++ kernels to accelerate complex, sequential model operations directly on the hardware.

 Desired skills and qualifications

  • Enrolled full-time student (d/f/m), in the area of Electrical/Electronics Engineering, Computer Engineering, Communications Engineering, Aerospace Engineering or an equivalent field of study.

  • Strong knowledge of deep learning frameworks (e.g., PyTorch, TensorFlow).

  • Proficiency in core programming languages, specifically Python and C/C++.

  • Desire to learn embedded processing platforms and FPGA tools like AMD Xilinx Vitis/Vivado.

  • Excellent written and spoken English for technical documentation and communication; German is a plus.

  • Ability to work independently and cooperate well within a team.

  • Strong problem-solving skills and good attention to detail.

  • Knowledge of satellite communications and/or 5G/6G networks is a plus.

Please upload the following documents: cover letter, CV, relevant transcripts, enrollment certificate. 

Not a 100% match? No worries! Airbus supports your personal growth.

Take your career to a new level and apply online now!

#MYCYM 

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Company:

Airbus Defence and Space GmbH

Employment Type:

Final-year Thesis

-------

Experience Level:

Student

Job Family:

Support to Management <JF-FA-ES>

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.

Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to emsom@airbus.com.

At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.

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