Software Engineer, AI and DL Kernel Libraries

Responsibilities

• Develop production-quality software that ships as part of NVIDIA's AI software stack, including cuDNN, FlashInfer, and optimized support for large language model inference workloads.
• Innovate and develop new AI systems technologies for efficient inference, with a focus on performance, scalability, maintainability, and usability.
• Design, implement, and optimize kernels for high-impact AI workloads across LLM inference, generative AI, computer vision, autonomous driving, and recommender systems.
• Design and implement extensible software abstractions for deep learning libraries, LLM serving engines, and runtime systems.
• Build and improve just-in-time compilation, code generation, and runtime technologies for performance-critical GPU workloads.
• Analyze workload performance, tune current software, and propose improvements to future software and hardware-software interfaces.
• Collaborate closely with engineers across deep learning frameworks, libraries, kernels, compilers, and GPU architecture teams at NVIDIA.
• Contribute to open-source communities and ecosystem integrations where relevant, including projects such as FlashInfer, vLLM, and SGLang.
• What we need to see
• Master's degree in Computer Science, Electrical Engineering, or a related field, or equivalent experience.

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