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.

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