Deep Learning Software Engineer, FlashInfer

Deep Learning Software Engineer, FlashInfer at NVIDIA

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

We're looking for outstanding AI systems engineers to develop groundbreaking technologies in the inference systems software stack! We build innovative AI systems software to accelerate for AI inference. As a member of the team, you'll develop libraries, code generators, and GPU kernel technologies for NVIDIA's hardware architecture. This means designing and building things like new abstractions, efficient attention kernel implementations, new LLM inference runtimes components, and kernel code generators to accelerate large language models, agents, and other high-impact AI workloads.

What You'll Be Doing

• Innovating and developing new AI systems technologies for efficient inference
• Designing, implementing, and optimizing kernels for high impact AI workloads
• Designing and implementing extensible abstractions for LLM serving engines
• Building efficient just-in-time domain specific compilers and runtimes
• Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries, kernels, and GPU arch teams
• Contributing to open source communities like FlashInfer, vLLM, and SGLang

What We Need To See

• Bachelor's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); PhD are preferred
• Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc) and ideally inference engines and runtimes such as vLLM, SGLang, and MLC.
• Strong Python and C/C++ programming skills

Ways To Stand Out From The Crowd

• Background in domain specific compiler and library solutions for LLM inference and training (e.g. FlashInfer, Flash Attention)
• Expertise in inference engines like vLLM and SGLang
• Expertise in machine learning compilers (e.g. Apache TVM, MLIR)
• Strong experience in GPU kernel development and performance optimizations (especially using CUDA C/C++, cuTile, Triton, or similar)
• Open source project ownership or contributions

Key skills/competency

• AI Systems
• Deep Learning Inference
• GPU Kernel Development
• LLM Optimization
• C/C++ Programming
• Python Programming
• Deep Learning Frameworks (PyTorch, JAX)
• Machine Learning Compilers (TVM, MLIR)
• CUDA
• Open Source Contribution