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What you’ll be doing:
Collaborate with cross-functional teams to understand requirements and contribute to the design and architecture of NVIDIA DirectML drivers.
Develop and implement high-quality, efficient, and reliable NVIDIA DirectML drivers following the best software development practices adhering to industry standards.
Identify and resolve performance bottlenecks for cutting-edge deep learning models in computer vision, generative AI, and other related fields.
Debug and resolve driver-related issues to ensure smooth functionality across multiple GPU architectures and platforms.
Collaborate with Microsoft to drive the advancements in ONNX and DML runtimes and ensure seamless integration with NVIDIA DirectML driver.
Build and contribute to performance profiling tools that improves the efficiency of the performance analysis workflow.
Ensure the effective deployment of essential directed tests and models through collaboration with the automation team, thereby ensuring the robustness of automated testing.
What we need to see:
Bachelor's, Master's, or PhD in Electrical Engineering, Computer Science/Engineering, Mathematics, Physics, or a related field (or equivalent experience).
5+ years of industry experience with proficiency in developing and optimizing DirectML drivers or similar graphics and machine learning drivers such as DirectX, Vulkan, or CUDA.
Familiarity with GPU hardware architecture, shader programming, and parallel processing techniques.
Excellent C++ programming and debugging skills with a strong understanding of data structures and algorithms.
Familiarity with deep learning frameworks such as PyTorch and TensorFlow and exposure to large language models and transformer architectures.
Strong analytical and problem-solving abilities, with the capacity to multitask effectively in a multifaceted environment.
Outstanding written and oral communication skills, enabling effective collaboration with management and engineering teams.
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