GPU Software Engineer (HPC / Deep Learning Optimization)

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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

Mandatory Skills Description:

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 Skills Description:

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)

Languages:

English: C1 Advanced