Job Description, Responsibilities & Requirements
About the Position
We are seeking a GPU Software Engineer with expertise in HPC and Deep Learning optimization for the Windows platform. Join our team to enhance GPU-based workloads.
Responsibilities
- Develop, optimize, and maintain GPU compute kernels using C++ and a GPU programming framework (CUDA, HIP, OpenCL, SYCL, DirectCompute / HLSL compute shaders, Metal compute, or equivalent).
- Profile GPU workloads and tune memory, compute, and latency to improve performance and efficiency.
- Analyze performance bottlenecks and apply targeted optimizations.
- Debug and resolve performance and stability issues.
- Apply kernel optimization to HPC or Deep Learning inference pipelines where needed.
- Collaborate with engineers, QA, and stakeholders.
- Follow coding standards and contribute to technical documentation.
Requirements
- Hands on experience writing and optimizing GPU compute kernels in at least one framework: CUDA, HIP, OpenCL, SYCL, DirectCompute / HLSL compute shaders, Metal compute, or equivalent.
- Ability to profile and performance tune GPU code (memory, compute, latency) as part of that work.
Nice to Have
- Strong knowledge of C++
- Experience with HPC or Deep Learning inference optimization
- Experience with profiling tools (Nsight, Radeon GPU Profiler, PIX, etc.)
- Experience with Deep Learning frameworks (TensorRT, ONNX Runtime, PyTorch, DirectML, etc.)
- Understanding of graphics pipelines and rendering basics
- Experience with a graphics API (DirectX, Vulkan, Metal, etc.)
- Experience with Windows platform GPU development
- Experience with CI/CD, version control, or automated testing
We Offer
- Opportunity to work on cutting-edge GPU computing projects
- Collaborative and innovative work environment
- Competitive compensation package
About the Company
Luxoft is a global technology services company that specializes in software engineering, embedded systems, and digital transformation. We are committed to delivering high-quality solutions to our clients across various industries.
Application
Interested candidates are encouraged to apply with their updated resume and portfolio showcasing relevant experience in GPU programming and optimization.