Note: The job is a remote job and is open to candidates in USA. NVIDIA is hiring a Senior Software Engineer for its TensorRT team to advance high-performance AI inference on NVIDIA GPUs. The role focuses on GPU code generation, compiler and runtime optimization, workload profiling, and developing inference software and tools.
Responsibilities
- Design and implement efficient GPU code generation techniques in TensorRT that balance 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 robust, maintainable software in C++, and Python for tooling, testing, and performance analysis
- Collaborate with GPU architects, kernel developers, compiler engineers, and deep learning experts to guide hardware and software design
Skills
- BS, MS, or PhD in Computer Science, Computer Engineering, or a related field, or equivalent experience
- 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
- A rigorous approach to performance analysis and debugging, with the ability to validate numerical correctness and explain performance tradeoffs
- Strong problem-solving and communication skills, and the ability to work independently and collaborate across teams
- Experience developing or optimizing GPU kernels using CUDA, Triton, CuTe DSL, CUTLASS, or other GPU programming languages
- Experience with MLIR compiler infrastructure, familiarity with intermediate representations, lowering, optimization passes, and GPU code generation
- Familiarity with NVIDIA Tensor Core architecture, mixed-precision computation, quantization, or low-level GPU performance analysis using tools such as NVIDIA Nsight
- Experience developing inference frameworks such as PyTorch, JAX, ONNX Runtime, TensorRT, TensorRT-LLM, vLLM, and SGLang
- A track record of measurable performance improvements in production software or contributions to GPU programming and compiler projects
Benefits
- Eligible for equity
- Hybrid work arrangement
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