Real-Time Radar GPU Architect & CUDA Engineer

Intelligent Employment; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Résumé du poste

Gallium Defense is seeking a GPU Architect & Engineer to own the GPU-hosted compute stack, from kernel design to memory management, and to develop and optimize CUDA functions at the heart of radar signal processing.

You will work with the SW & AI team, collaborating with RF, electronics, and systems engineering to turn demanding latency and throughput targets into robust, field-ready compute solutions for real-world testing.

Qualifications

• Master's degree in Computer Science, Electrical Engineering, or a related field, or equivalent hands‑on experience.
• 3+ years of hands‑on CUDA development with architectural judgment across a GPU pipeline.
• Deep CUDA expertise: writing, optimizing, and profiling GPU code.
• Evidence of architectural thinking on GPU‑hosted systems and AI workloads.
• Solid C++, experience with embedded Linux and real‑time constraints.
• Nice to have: radar or signal processing background; ML edge inference (TensorRT, quantization).
• Fluent in French; proficient in technical English.

Responsabilités

• GPU Software Architecture: own the GPU software structure, kernel design, memory strategy and scheduling.
• CUDA Development & Optimization: design, implement and optimize signal processing kernels for latency and throughput.
• SW / AI Integration on GPU: unify software and AI into a single performant runtime on the GPU.
• Performance, Quality & Field Support: set perf practices, write tests, review code, support field experiments.

Connaissances

CUDA development

GPU architecture

C++ programming

Embedded Linux

Real-time systems

French language

Technical English

Edge ML inference

Formation

Master's degree in CS/EE

Outils

TensorRT

Profiling tools

CUDA toolkit

Build systems

Description du poste

Gallium Defense is seeking a GPU Architect & Engineer to own the GPU-hosted compute stack, from kernel design to memory management, and to develop and optimize CUDA functions at the heart of radar signal processing.

You will work with the SW & AI team, collaborating with RF, electronics, and systems engineering to turn demanding latency and throughput targets into robust, field-ready compute solutions for real-world testing.