CUDA C++ engineers can design GPU kernels at Baseten, optimizing matrix multiplication and attention for production machine learning inference. Work model is not specified.As a GPU Kernel Engineer, you will support Baseten’s Model Performance team and its inference stack. You will write CUDA and PTX code, apply GPU architecture knowledge, and optimize up-to-date AI workloads. The work includes collaboration with research teams and production systems.Key Responsibilities:

Design high-performance kernels for matrix multiplicationsOptimize attention mechanisms and mixture-of-experts routingApply memory coalescing and warp-level programmingUse tensor cores and compute-memory overlapContribute to internal and open-source GPU librariesRequirements:

Understand GPU architecture and programming paradigmsKnow memory hierarchy and thread organizationMitigate race conditions using synchronization techniquesDemonstrate C++ proficiency and profiling-tool experienceUnderstand CUDA C++ APIs and bandwidth optimizationBuild Baseten’s inference performance through CUDA C++, GPU architecture, kernel optimization, and production-focused machine learning systems.

📌 Gpu Kernel Engineer Cuda C++ (Winnipeg)
🏢 Baseten
📍 Winnipeg