1 day ago
Base Salary
$152k - $288k/yr
Responsibilities
- Design and implement GPU code generation techniques in TensorRT while balancing generated-code performance, compilation overhead, and startup latency.
- Develop compiler optimizations including operator fusion, dynamic scheduling, and specialization for model shapes, data types, and GPU architectures.
- Profile workloads and analyze generated GPU code to identify bottlenecks and guide compiler and runtime improvements.
- Develop maintainable C++ and Python software for tooling, testing, and performance analysis.
- Collaborate with GPU architects, kernel developers, compiler engineers, and deep learning experts on hardware and software design.
Requirements
- Bachelor’s, master’s, or doctoral degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
- At least 4 years of relevant software development experience, including contributions to a substantial codebase or project.
- Strong proficiency in C++ and experience building performance-critical software.
- Understanding of GPU architecture and parallel programming concepts, including memory hierarchies, thread execution, synchronization, and resource utilization.
- Ability to perform rigorous performance analysis and debugging, validate numerical correctness, and explain performance tradeoffs.
- Strong problem-solving and communication skills, with the ability to work independently and collaborate across teams.
- Preferred experience with CUDA, Triton, CuTe DSL, CUTLASS, MLIR, GPU code generation, NVIDIA Tensor Core architecture, mixed precision, quantization, NVIDIA Nsight, and inference frameworks such as PyTorch, JAX, ONNX Runtime, TensorRT, TensorRT-LLM, vLLM, and SGLang.
- Preferred track record of measurable performance improvements in production software or contributions to GPU programming and compiler projects.
Benefits
- Hybrid work arrangement.
- Eligible for equity and benefits.
Categories
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.