GPU Software Engineer (HPC / Deep Learning Optimization)
Project description
We are looking for a Software Engineer focused on GPU computing, HPC workloads, and Deep Learning inference optimization on Windows platform. The project is aimed at improving performance and efficiency of GPU-based workloads, including compute kernels and inference pipelines. The role is not limited to graphics APIs and is suitable for candidates with strong experience in CUDA, OpenCL, or similar technologies, as well as shader-based optimization.
Responsibilities
- Develop and optimize GPU workloads using C++ and GPU programming frameworks Improve performance of HPC or Deep Learning inference pipelines Analyze bottlenecks and optimize memory, compute, and latency Perform GPU profiling and performance tuning Debug and fix performance and stability issues Collaborate with engineers, QA, and stakeholders Follow coding standards and contribute to technical documentation
SKILLS
Must have
- Familiarity with shader development (HLSL, GLSL etc) OR kernel development (CUDA, HIP, OpenCL, etc) Experience with HPC or Deep Learning inference optimization Experience with profiling tools (Nsight, Radeon GPU Profiler, PIX, etc.)
Nice to have
Strong knowledge of C++ Experience with Deep Learning frameworks (TensorRT, ONNX Runtime, PyTorch, etc.) Understanding of graphics pipelines and rendering basics Experience with a graphics API (DirectX, Vulkan, Metal, etc) Experience with CI/CD, version control, or automated testing Experience with GPGPU development (CUDA/HIP/OpenCL)
