Thales

1 month ago

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

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Embedded Software Engineer for accelerated computing develops high-throughput signal processing on state-of-the-art embedded GPUs, building real-time streaming pipelines from FPGA front-ends to GPU processing chains. You will optimize algorithms, maintain OS images, verify with Python/C++ references, and collaborate in a small interdisciplinary team to push edge AI capabilities in defense-related radar and imaging applications.

Location: Germany

Workplace: Hybrid

Employment Type: Full time · 18 months

Job Function: Software Engineering

Key Responsibilities

•Implement and optimize high-throughput signal processing algorithms (FFT-based processing, filtering, detection and estimation) as highly parallel GPU kernels.
•Design zero-copy / DMA-based ingest paths from FPGA-based front-ends into GPU memory and build deterministic, real-time streaming pipelines with buffering and precise time-stamping.
•Evaluate and adopt vendor SDKs, libraries and pipeline frameworks for accelerated sensor processing and edge AI inference; maintain OS images and deployment for embedded compute modules.
•Profile and benchmark systematically; validate numerically and bit-true against Python/C++ reference implementations; contribute unit/integration tests and CI/CD integration.
•Collaborate in a small interdisciplinary prototyping team; travel ~15% for integration and measurement campaigns.

Travel: Low travel

Key Requirements

•Completed technical studies, e.g. in computer science or electronic 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).
•Experience with embedded GPU / edge-AI compute modules and their SDK ecosystems advantageous.

Experience:DefenseEdge AIEmbedded systems

Education:Bachelor's

Skills:C++CUDAPythonLinuxGPUEmbedded systemsDMACI/CDOS images

Languages:GermanEnglish

Tech Stack:C++CUDAPythonLinuxGPUEmbedded systemsDMACI/CDOS images

Company Brief

Thales

Designs and delivers advanced systems and services for aerospace, defence, security, and digital identity and cybersecurity markets, serving government and commercial customers worldwide.

Industry: Defense Technology

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Paris, France

Founded: 2000

Website LinkedIn

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Thales

1 month ago

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

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: Germany

Workplace: Hybrid

Employment Type: Full time · 18 months

Job Function: Software Engineering

Key Responsibilities

•Implement and optimize high-throughput signal processing algorithms (FFT-based processing, filtering, detection and estimation) as highly parallel GPU kernels.
•Design zero-copy / DMA-based ingest paths from FPGA-based front-ends into GPU memory and build deterministic, real-time streaming pipelines with buffering and precise time-stamping.
•Evaluate and adopt vendor SDKs, libraries and pipeline frameworks for accelerated sensor processing and edge AI inference; maintain OS images and deployment for embedded compute modules.
•Profile and benchmark systematically; validate numerically and bit-true against Python/C++ reference implementations; contribute unit/integration tests and CI/CD integration.
•Collaborate in a small interdisciplinary prototyping team; travel ~15% for integration and measurement campaigns.

Travel: Low travel

Key Requirements

•Completed technical studies, e.g. in computer science or electronic 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).
•Experience with embedded GPU / edge-AI compute modules and their SDK ecosystems advantageous.

Experience:DefenseEdge AIEmbedded systems

Education:Bachelor's

Skills:C++CUDAPythonLinuxGPUEmbedded systemsDMACI/CDOS images

Languages:GermanEnglish

Tech Stack:C++CUDAPythonLinuxGPUEmbedded systemsDMACI/CDOS images

Company Brief

Thales

Designs and delivers advanced systems and services for aerospace, defence, security, and digital identity and cybersecurity markets, serving government and commercial customers worldwide.

Industry: Defense Technology

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Paris, France

Founded: 2000

Website LinkedIn