NVIDIA has reshaped computer graphics, PC gaming, and accelerated computing for over 25 years. The invention of the GPU in 1999 propelled the growth of the PC gaming market, redefined computer graphics, and transformed parallel computing. Today, we are harnessing the boundless potential of AI to define the next phase of accelerated computing. GPU deep learning sparked the modern AI revolution, becoming the pivotal driver of intelligent applications in productivity, gaming, and creative sectors, solidifying NVIDIA's position as the foremost "AI computing company." Achieving unprecedented feats demands vision, innovation, and the world's top talent.

We are looking for a passionate and exceptional engineer for the Windows AI (WinAI) team. Your role will involve developing inference runtimes, optimizing GenAI pipelines and inference backends, and algorithms for optimizing models to seamlessly integrate AI into games and applications for Windows PCs. The role requires a blend of AI knowledge and system software skills.

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.

• Perform 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.

• Identify and implement compute and memory optimizations across the full AI inference stack on RTX Windows PC to ensure the best performance and quality of service.

• Develop model compression and fine-tuning techniques to reduce resource consumption and improve performance, enabling efficient deployment and better user experience.

• Design and implement an optimized framework for running AI NPCs in gaming applications as part of the NVIDIA ACE Platform.

• 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 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 of modern techniques in Machine Learning, Deep Neural Networks, and Generative AI with relevant 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.

• Consistent track record of delivering end-to-end products with geographically distributed teams in multinational product companies.

We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

The base salary range is 120,000 USD - 230,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.