Gallium Defense | GPU

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