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Embedded Software Engineer (m/f/d) GPU & edge AI Signal Processing
Thales —Ditzingen
Experience with high-rate sensor data (radar, lidar, imaging, software-defined radio) advantageous. The Group invests more than €4,5 billion per year in…

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Embedded Software Engineer (m/f/d) GPU & edge AI Signal Processing

Thales -
Ditzingen

Jetzt bewerben

Details zur Stelle

Vollzeit

Qualifikationen

CI/CD
Informatik
Signalverarbeitung
FPGA
Forschungserfahrung
Kernels
C++
SDKs
Cyber Security
Künstliche Intelligenz
Python

Vollständige Stellenbeschreibung

Location: DITZINGEN SRA OME, Germany

We say HI*

Thales in Germany is part of an internationally leading technology group in the defence and security, aerospace as well as cyber security and digital identity markets.

**Say HI* – to your career as**

Embedded Software Engineer (m/f/d) GPU & edge AI Signal Processing

In Ditzingen #LI-HYBRID

In Ditzingen, you will encounter security solutions for monitoring and safeguarding borders and for border controls, protection of civil and military facilities and tactical communication. This is the right place for you if you want to work with us on practical highly mobile radars for ground and coastal monitoring or night vision goggles and multifunctional heat imaging equipment. Join the Thales expert team for radar, optronic vision systems for armoured military vehicles or for protecting the field camps of the German Armed Forces. We are happy to have you on board!

Your mission as Embedded Software Engineer (m/f/d):

As Embedded Software Engineer for accelerated computing you bring our real-time sensor processing chain to life on state-of-the-art embedded GPU compute modules: you implement and optimize high-throughput signal processing algorithms for massively parallel execution, build low-latency streaming pipelines from the digital front-end into the processing chain, and continuously push the limits of what modern edge hardware can deliver – with data rates of several GB/s and hard latency budgets.

Algorithm implementation & optimization
- Implement signal processing algorithms (FFT-based processing, filtering, detection and estimation stages) as highly parallel GPU kernels
- Optimize for throughput and latency: memory hierarchy, kernel fusion, asynchronous streams/graphs, mixed precision
Streaming & data movement
- Design zero-copy / DMA-based ingest paths from FPGA-based front-ends into GPU memory
- Build deterministic, real-time-capable streaming pipelines including buffering, backpressure handling and precise time-stamping
Platform & framework work
- Evaluate and adopt state-of-the-art vendor SDKs, libraries and pipeline frameworks for accelerated sensor processing and edge AI inference
- Maintain OS images, board support and deployment for the embedded compute modules
Quality & verification
- Profile and benchmark systematically; validate numerically and bit-true against Python/C++ reference implementations
- Contribute unit/integration tests, CI/CD integration and documentation

We are looking forward to:

Completed technical studies, e.g. in computer science or electronical engineering
Strong modern C++ (C++17 or newer) on Linux
Solid hands-on CUDA / GPU computing experience: kernel development, profiling and performance optimization
Understanding of real-time data streaming and heterogeneous memory architectures (DMA, pinned/unified memory, peer-to-peer transfers)
Fundamentals of digital signal processing
Experience with embedded GPU / edge-AI compute modules and their SDK ecosystems advantageous
Experience with graph- or pipeline-based streaming frameworks for sensor or media processing advantageous
Python for prototyping, validation and tooling advantageous
Experience with high-rate sensor data (radar, lidar, imaging, software-defined radio) advantageous
Strong team and communication skills in a small, interdisciplinary prototyping team
Analytical and structured way of thinking and working
Self-directed, proactive working style with a high level of ownership
Precision and quality awareness, especially in verification and interface definition
Pragmatic, hands-on prototyping mindset – willingness to iterate fast and learn from hardware
Willingness to travel for integration and measurement campaigns (~15%)
Very good German and English skills

The Group invests more than €4,5 billion per year in Research & Development in key areas, particularly for critical environments, such as Artificial Intelligence, cybersecurity, quantum and cloud technologies.

In 2025, the Group generated sales of €22.1 billion.

For our more than 85,000 employees in 65 countries we open up visionary perspectives, realise individual career paths and enable creative freedom. This is achieved with courage, versatility and the firm intention to make the demanding challenges of our time safer and more inclusive. With our sustainable value-focused management we support diversity actively.

Say HI* – Your journey to us

At times of change our international teams are ready to meet the complexity of today with the industry-leading technologies of tomorrow. Will you be part of it? Your Talent Acquisition contact Maria Gaissert is looking forward to your online application.

Maria Gaissert – Talent Acquisition Partnerin #LI-MG1

+49 172 8281399

Human Intelligence

Jetzt bewerben

Erweiterte Suche

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