CUDA Programmer
Location: Waukesha WI
We are seeking a skilled CUDA Programmer to design develop and optimize high-performance applications on NVIDIA GPUs. The role focuses on accelerating compute-intensive workloads optimizing memory usage and collaborating with system and application teams to maximize GPU performance.
Key Responsibilities
- Profile and tune GPU applications for performance memory efficiency and scalability.
- Work with CPU GPU parallel programming models and optimize data transfer.
- Leverage NVIDIA libraries (CUDA cuBLAS cuDNN NCCL as applicable).
- Collaborate with system compute or AI/ML teams to integrate GPU-accelerated components.
- Debug GPU kernels and address performance bottlenecks using NVIDIA profiling tools.
- Ensure portability and performance across different NVIDIA GPU architectures.
Required Skills
- Strong experience in CUDA programming and parallel computing concepts.
- In-depth understanding of NVIDIA GPU architecture (threads warps SMs memory hierarchy).
- Proficiency in C/C for high-performance computing.
- Experience with CUDA profiling and debugging tools (Nsight nvprof).
- Solid understanding of multi-threading memory optimization and performance tuning.
Preferred Skills
- Experience with AI/ML HPC or graphics workloads on GPUs.
- Familiarity with multi-GPU programming and communication frameworks (NCCL MPI).
- Exposure to Python bindings (CUDA Python PyTorch extensions).
- Experience with Linux-based development environments.
CUDA Programmer Location: Waukesha WI We are seeking a skilled CUDA Programmer to design develop and optimize high-performance applications on NVIDIA GPUs. The role focuses on accelerating compute-intensive workloads optimizing memory usage and collaborating with system and application teams to max...
CUDA Programmer
Location: Waukesha WI
We are seeking a skilled CUDA Programmer to design develop and optimize high-performance applications on NVIDIA GPUs. The role focuses on accelerating compute-intensive workloads optimizing memory usage and collaborating with system and application teams to maximize GPU performance.
Key Responsibilities
- Profile and tune GPU applications for performance memory efficiency and scalability.
- Work with CPU GPU parallel programming models and optimize data transfer.
- Leverage NVIDIA libraries (CUDA cuBLAS cuDNN NCCL as applicable).
- Collaborate with system compute or AI/ML teams to integrate GPU-accelerated components.
- Debug GPU kernels and address performance bottlenecks using NVIDIA profiling tools.
- Ensure portability and performance across different NVIDIA GPU architectures.
Required Skills
- Strong experience in CUDA programming and parallel computing concepts.
- In-depth understanding of NVIDIA GPU architecture (threads warps SMs memory hierarchy).
- Proficiency in C/C for high-performance computing.
- Experience with CUDA profiling and debugging tools (Nsight nvprof).
- Solid understanding of multi-threading memory optimization and performance tuning.
Preferred Skills
- Experience with AI/ML HPC or graphics workloads on GPUs.
- Familiarity with multi-GPU programming and communication frameworks (NCCL MPI).
- Exposure to Python bindings (CUDA Python PyTorch extensions).
- Experience with Linux-based development environments.
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