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Partnering with NVIDIA software, research, architecture and product teams, aligning strategies and technical needs for fostering the ecosystem of AI on a Windows RTX PC.
Perform in-depth analysis and optimization of AI models, data processing pipelines, and inference backends to ensure the best performance on current and next-generation GPU architectures.
Identify, research and implement compute and memory optimizations techniques, perform competitive analysis and work with various training and inference frameworks teams to incorporate these optimizations in the various training and inferencebackends.
Collaborate with open source and ISV developers working on GenAI (like large language models, stable diffusion etc.) and develop reference projects and libraries using various backends like tensorrt-llm that would enable developers to run these products natively on windows on GPU with optimalperformance
Fine-tune AI models, use various compression techniques such as quantization, distillation and pruning to fit the models to user's windows edge devices and enhance the performance of inferencing engines.
Collaborate with Microsoft to drive the advancements in APIs, AI frameworks, and platforms for developing and deploying AI inferencing applications.
Ensure the effective deployment of directed tests through collaboration with the automation team, thereby ensuring the robustness of automated testing.
What We NeedSee:
Bachelor's, Master's, or PhD in Computer Science, Software Engineering, Mathematics, or a related field (or equivalent experience).
Excellent C++ programming and debugging skills with a strong understanding of data structures and algorithms.
4+ years of shown experience with proficiency in AI inferencing pipelines and applications using ML/DL frameworks like ONNX RT, DirectML, PyTorch, Tensor RT etc.
Strong analytical and problem-solving abilities, with the capacity to multitask effectively in a dynamic environment.
Outstanding written and oral communication skills, enabling effective collaboration with management and engineering teams.
Ways To Stand OutCrowd:
Understanding of modern techniques in Machine Learning, Deep Neural Networks, and Generative AI with relevant contributions to major open-source projects will be a plus.
Consistent track record of delivering end-to-end products with geographically distributed teams in multinational product companies.
Proficiency in lower-level system/GPU programming, CUDA, developing high performance systems
Hands on experience with building applications using APIs like ONNX RT, DirectML, DirectX, PyTorch, TensorRT, Vulkan
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