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As a Windows AI Engineer, you will be instrumental in developing inference runtimes, optimizing GenAI pipelines and inference backends, and devising algorithms that flawlessly incorporate AI into games and applications for Windows. This position requires a unique blend of AI knowledge and system software skills, making it an excellent fit for individuals who have a strong desire to shape the future of computing!
What You’ll Be Doing:
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.
Performing in-depth analysis and optimization of AI models, AI frameworks, data processing pipelines, and inference backends to ensure the best performance on current and next-generation GPU architectures.
Identifying and implementing compute and memory optimizations across the full AI inference stack on RTX Windows PC.
Developing model compression and fine-tuning techniques to reduce resource consumption and improve performance, enabling efficient deployment and better user experience.
Designing and implementing an optimized framework for running AI NPCs in gaming applications as part of the NVIDIA ACE Platform.
Collaborating with Microsoft to drive advancements in APIs, AI frameworks, and platforms for developing and deploying AI inferencing applications.
Ensuring the effective deployment of directed tests 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 Computer Science, Software Engineering, Mathematics, or a related field (or equivalent experience).
2 years of experience in AI inferencing pipelines and applications using ML/DL frameworks like PyTorch, ONNX Runtime, DirectML preferred.
Excellent C++ programming and debugging skills with a strong understanding of data structures and algorithms.
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 Out From The Crowd:
Understanding Machine Learning, Deep Neural Networks, and Generative AI with meaningful contributions to major open-source projects will be a plus.
Proficiency in lower-level system/GPU programming, CUDA, and developing high-performance systems.
Hands-on experience with building applications using graphics APIs like OpenGL, DirectX, Vulkan, etc.
Proven track record of delivering end-to-end products with geographically distributed teams in multinational product companies.
You will also be eligible for equity and .
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