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About Gallium Defense
At Gallium Defense, they are rewriting the rules of air defense in the context of rapidly evolving drone threats. They design and build next-generation, military-grade radar systems that deliver high-performance 3D detection at competitive pricing — supporting growing demand and closing critical capacity gaps.
The Role:
As GPU / CUDA Architect & Engineer at Gallium Defense, you will report to the SW & AI Lead and be a full member of their SW & AI team. You will own the architecture of their GPU-hosted compute — from kernel design to how work is scheduled and memory is managed on the device — and develop and optimize the CUDA functions at the heart of our radar signal-processing. You'll partner closely with their SW architect to make sure that design serves the system as a whole. Hands-on and close to the end users and the experimentation field, you will build together with the rest of the SW & AI team — which contributes alongside the other modules and teams to form a single product team — turning demanding latency and throughput targets into robust, field-ready compute.
Key Responsibilities
GPU Software Architecture: Take full technical ownership of how their software and AI are structured on the GPU itself — kernel design, memory strategy, scheduling and work partitioning across the device — so processing and AI run together within tight real-time budgets. You'll work hand-in-hand with their SW architect on how that GPU-side design fits the broader system.
CUDA Development & Optimization: Design, implement, and optimize the signal processing functions — profiling and tuning for latency, throughput, and memory to meet operational requirements.
SW / AI Integration on GPU: Bring the software and AI together into a single performant runtime on the GPU, working hand-in-hand with the rest of the SW & AI team and with the other modules and teams on clean interfaces.
Performance, Quality & Field Support: Set the performance-engineering practices (benchmarking, profiling, regression tracking), write tests, review code, and support field frequent field experiments — debugging GPU and compute issues in real environments and iterating rapidly.
Profile & Requirements
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 the architectural judgment to show for it — you've structured compute, memory, and data flow across a GPU pipeline (must-have).
Deep CUDA expertise: writing, optimizing, and profiling GPU code.
Evidence of architectural thinking on GPU-hosted systems — you can point to real decisions you drove on how software and AI workloads are structured to run efficiently on a GPU.
Solid C++, experience with embedded Linux and real-time constraints.
Nice to have: experience with radar or signal processing, or adjacent domains (e.g. RF).
Nice to have: experience deploying or optimizing ML models for edge inference (e.g. TensorRT, quantization, mixed precision).
Fluent in French; proficient in technical English.
Why Join Gallium Defense?
The drone threat is growing faster than the systems designed to counter it. At Gallium, they’re democratizing C-UAS radars at scale — affordable, rugged, and high-performance — that give civil and defense operators a real answer. They think the way radar is built needs to change, and they’re proving it’s possible.
Build products that directly contribute to protecting our future
Own critical design decisions with visible impact on the final system
Collaborate with experts across RF, electronics, FPGA, software, and systems engineering
Experiment directly in the field with civil and military end-users
See your work move rapidly from concept to deployed system
Shape both the product and engineering culture of an ambitious deep-tech company
If you're excited about solving complex signal-processing challenges and building systems with tangible real-world impact, we'd love to hear from you!