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 multiplications Optimize attention mechanisms and mixture-of-experts routing Apply memory coalescing and warp-level programming Use tensor cores and compute-memory overlap Contribute to internal and open-source GPU libraries Requirements:

Understand GPU architecture and programming paradigms Know memory hierarchy and thread organization Mitigate race conditions using synchronization techniques Demonstrate C++ proficiency and profiling-tool experience Understand CUDA C++ APIs and bandwidth optimization Build Baseten’s inference performance through CUDA C++, GPU architecture, kernel optimization, and production-focused machine learning systems.

#J-18808-Ljbffr

📌 GPU Kernel Engineer CUDA C++ (Winnipeg)
🏢 Baseten
📍 Winnipeg