Senior Software Engineer, GPU Code Generation for Machine Learning Inference
NVIDIA· Engineer, Sys SW
Hybrid (Santa Clara, CA), Remote$152k - $241.5kfull-timePosted 4d ago
About the role
Senior software engineer role on the TensorRT team focused on high-performance GPU code generation, just-in-time compilation, and inference optimization for generative AI models on NVIDIA GPUs.
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.
Qualifications
- 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.
Skills
Required:C++PythonGPU architectureCompiler optimizationsPerformance analysisCollaboration
Benefits
- equity
- benefits (as per company policy)
Last updated Oct 23, 2026. Interested? Apply on the company site.
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