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