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.

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