About this role
GPU Software Engineer
Project description We are looking for engineers to join a GPU software team working at the intersection of real-time graphics and machine learning (upscaling, denoising, artifact suppression for interactive visual applications). The work spans rendering pipelines, ML model integration and GPU performance optimization, in collaboration with graphics and driver teams. Responsibilities Develop and optimize rendering and/or ML inference components for real-time visual pipelines (DX12, Vulkan, ONNX-based stacks). Profile GPU workloads and tune for latency, memory and throughput. Integrate ML models (super-resolution, denoising) into graphics pipelines. Evaluate output quality using objective and perceptual metrics (PSNR/SSIM, LPIPS) and visual regression tooling. Author clean, testable, reproducible code; collaborate with graphics, ML and platform teams. Skills Must have 4+ years of software engineering experience with C++ (for ML-focused candidates: strong Python with working-level C++). Solid GPU fundamentals: pipeline, synchronization and memory models, performance trade-offs. Deep expertise in at least one of the two areas: (a) real-time graphics: DX12 and/or Vulkan, shader authoring (HLSL/GLSL), rendering techniques, GPU debugging/profiling (RenderDoc, PIX, Radeon GPU Profiler), OR (b) image ML: PyTorch, super-resolution/denoising/artifact-suppression models, inference deployment and optimization on GPU (ONNX Runtime or TensorRT, quantization). Working awareness of the other