Senior Software Engineer, GPU Code Generation for Machine Learning Inference

NVIDIA Corporation; California; Sur place; USD 152 000 - 288 000; Plein temps

Avantages offerts par ce poste

Equity

Benefits

Résumé du poste

NVIDIA Corporation seeks talented engineers to join the TensorRT team and advance high-performance AI inference on NVIDIA GPUs. You will design and implement GPU code generation and compiler optimizations, collaborating with architects and engineers to deliver optimized inference across models and hardware.

Ideal candidates have strong C++ proficiency, experience with GPU architectures, and a track record of performance improvements in production systems. Equity and benefits accompany the role.

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.

Responsabilités

• 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.

Connaissances

C++

Python

GPU architecture

Parallel programming

Performance analysis

Communication

Formation

BS/MS/PhD in CS/CE or related

Outils

CUDA

Triton

MLIR

Nsight

CUTLASS

CuTe DSL

Description du poste

NVIDIA is seeking talented engineers to join the TensorRT team and advance high-performance AI inference on NVIDIA GPUs. Our team develops software that accelerates state-of-the-art generative AI models for local and enterprise deployments. We solve challenging problems in GPU code generation, just-in-time compilation, and inference optimization to deliver high performance across diverse models and hardware configurations.

What You’ll Be Doing

• 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.

What We Need To See

• 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.

Ways To Stand Out From The Crowd

• 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.

At NVIDIA, you’ll work with engineers across GPU architecture, compilers, and AI software to solve demanding performance problems. If you are curious and enjoy understanding how hardware executes code and building software that pushes its capabilities, join us in shaping the future of generative AI inference.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 25, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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