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# HPC Performance Engineer

- **Company:** NVIDIA Ltd.
- **Location:** Remote, OR, United States (Remote available)
- **Experience:** Expert
- **Salary:** $152,000.0 - $241,500.0
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Application Performance Management, Assembly Language, C++ (Programming Language), Compilers, Nvidia CUDA, Computer Programming, System Configuration, Software Debugging, Device Drivers, Fortran (Programming Language), OpenMP, Software Engineering, Parallel Computation, Information Technology
- **Published:** October 16, 2026
- **Apply:** https://www.juju.com/job/1_ScrapingHub33470-JR2021671

## About the Role

What we need to see: + BS/MS or equivalent experience in Computer Science or a related engineering field. + 5+ years of programming experience. + Solid understanding of Fortran, C, C++, and programming techniques, especially for parallel architectures, preferably for compilers. + Experience with OpenACC, OpenMP, MPI, CUDA and Standard Language Parallelism. + Strong skills in performance analysis and tuning, as well as a broad understanding of parallel applications development tools and runtime environments. + Strong mathematical fundamentals, including linear algebra and numerical methods. + Understand performance considerations, tradeoffs, and impact. + Expert interpersonal skills, a logical approach to problem-solving, good time management, and task prioritization skills.
Excellent written and verbal communication skills, along with the ability to work in a dynamic development team.
Ways to stand out from the crowd: + You have a deep understanding of machine architectures and micro-architectures. + Experience with debugging and porting as well as assembly language programming is a significant advantage.

## Description

What you'll be doing: + Analyze the effect of different compilers and compiler optimizations on HPC application performance. + Evaluate whether and how the compiler and runtime can improve the performance of key HPC applications on CPU and CPU/GPU platforms. + Communicate limits of compiler capabilities with application engineering to guide the best path forward towards improving performance. + Port HPC applications to different platforms and programming models. + Evaluate the impact of NVHPC package components, device driver, and system configuration on application performance.