Full-Time
Senior HPC Performance Engineer
Posted on 6/6/2026
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
Compensation Overview
$184k - $287.5k/yr
Company Historically Provides H1B Sponsorship
Remote in USA + 4 more
More locations: Oregon, USA | California, USA | Texas, USA | Massachusetts, USA
Remote
 Software Engineering (1) |
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- BS/MS or equivalent experience in Computer Science or related engineering field.
- 8+ Years of programming experience.
- Solid understanding of Fortran/C/C++, as well as programming techniques, especially for parallel architectures; preferably for compilers
- Experience with OpenACC, OpenMP, MPI, and CUDA.
- 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, 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 product oriented team.
- Assist customers GPU accelerate HPC applications.
- Analyze High Performance Computing (HPC) applications to better understand their performance characteristics.
- Provide advise and drive compiler and applications engineering development teams based on the analysis of these HPC applications.
- 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.
- Experience is leading and/or managing projects is a plus.
NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.
Company Size
10,001+
Company Stage
IPO
Headquarters
Santa Clara, California
Founded
1993
Simplify's Take
What believers are saying
- Data center revenue grew 92% to $75.2 billion.
- OEM adoption of RTX Spark expands on-device AI demand.
- Multiple HBM4 suppliers support Vera Rubin production scaling.
What critics are saying
- China export controls already triggered a $4.5 billion H20 charge.
- Cisco-style valuation compression threatens shares if AI spending normalizes.
- AMD, Intel, and Qualcomm pressure RTX Spark expansion.
What makes NVIDIA unique
- CUDA and software lock developers into NVIDIA's GPU ecosystem.
- Blackwell spans data center, laptops, and AI systems.
- Full-stack AI infrastructure combines chips, networking, and software.
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