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High Performance Computing Hpc Analyst Jobs in Oregon

... High-performance computing (HPC) applications development * 3 year+ Floating point implementations of transcendental functions (sin, cos, tanh, elu, etc) * 1 year+ Algorithms for non-IEEE low ...

Our GPUs are being used in many of the largest high performance computing projects around the world ... NVIDIA's HPC Compiler team is looking to hire a Compiler Engineering Manager to join the team ...

Our GPUs are being used in many of the largest high performance computing projects around the world ... NVIDIA's HPC Compiler team is looking to hire a Compiler Engineering Manager to join the team ...

Our GPUs are being used in many of the largest high performance computing projects around the world ... NVIDIA's HPC Compiler team is looking to hire a Compiler Engineering Manager to join the team ...

Senior Fortran Compiler Engineer

OR · On-site +1

$104K - $143K/yr

... high-performance computing, then we want you. We're implementing Flang with a keen interest in high ... HPC community What we need to see: 6+ years experience working on a production Fortran compiler ...

Senior Fortran Compiler Engineer

Hillsboro, OR · On-site

$113K - $156K/yr

... high-performance computing, then we want you. We're implementing Flang with a keen interest in high ... HPC community What we need to see: 6+ years experience working on a production Fortran compiler ...

Senior Fortran Compiler Engineer

Hillsboro, OR · On-site

$113K - $156K/yr

NVIDIA's HPC compiler group wants to hire a Fortran compiler developer to join the team building ... high-performance computing, then we want you! We're implementing Flang with a keen interest in high ...

... high-performance computing (HPC), AI/ML, and enterprise environments. You will be embedded in the ... Engage in proactive problem prevention by analyzing field data to identify emerging patterns ...

Senior Engineer - Quantum Error Correction Libraries

OR · On-site +1

$122K - $161K/yr

... HPC and GPUs to the quantum computing ecosystem. If you are passionate about developing high-performance software and want to help us build libraries to significantly accelerate research and ...

Showing results 21-40

High Performance Computing Hpc Analyst information

What does a high performance computing HPC analyst do?

A High Performance Computing (HPC) Analyst is responsible for managing, optimizing, and supporting high-performance computing systems used in research, engineering, and data-intensive applications. Their work includes configuring hardware and software for clusters or supercomputers, troubleshooting system issues, and assisting users in running complex computational jobs efficiently. They also monitor system performance, recommend upgrades, and help ensure security and data integrity within HPC environments. HPC Analysts often collaborate with researchers and IT staff to achieve optimal performance for scientific or business computing tasks.

What are the key skills and qualifications needed to thrive as a high performance computing HPC analyst?

To thrive as a High Performance Computing (HPC) Analyst, you need a solid background in computer science, mathematics, or engineering, with expertise in parallel programming and Linux-based systems. Familiarity with technical tools such as MPI, OpenMP, job schedulers (like Slurm), and experience with various HPC architectures is typically required, and certifications in cloud or HPC systems can be advantageous. Strong problem-solving abilities, communication skills, and the capacity to work collaboratively with researchers and IT professionals are standout soft skills. These competencies are essential to efficiently optimize computational resources, troubleshoot issues, and enable groundbreaking research or data analysis in high-demand environments.

What are some common challenges faced by high performance computing HPC analysts when supporting users and systems?

High Performance Computing Analysts often encounter challenges such as troubleshooting complex hardware and software issues, optimizing application performance, and managing resource allocation for multiple users. Balancing the needs of researchers while maintaining system stability and security can be demanding, especially as workloads and technologies rapidly evolve. Additionally, effective communication with users from diverse scientific backgrounds is crucial to understand their requirements and provide tailored support.

What is the difference between High Performance Computing Hpc Analyst vs Data Analyst?

AspectHigh Performance Computing (HPC) AnalystData Analyst
Required CredentialsBachelor's degree in Computer Science, IT, or related field; certifications in HPC or related technologiesBachelor's degree in Statistics, Mathematics, or related field; certifications in data analysis tools
Work EnvironmentResearch labs, data centers, or IT departments focusing on large-scale computingBusiness, finance, healthcare, or marketing environments analyzing datasets
Employer & Industry UsageTech companies, research institutions, government agenciesCorporate sectors, consulting firms, healthcare providers

The main difference is that HPC Analysts focus on managing and optimizing high-performance computing resources for complex simulations and large datasets, while Data Analysts interpret data to generate insights for decision-making. HPC Analysts require specialized knowledge of computing infrastructure, whereas Data Analysts focus more on data visualization and statistical analysis.

What cities in Oregon are hiring for High Performance Computing Hpc Analyst jobs?

Cities in Oregon with the most High Performance Computing Hpc Analyst job openings:

Infographic showing various High Performance Computing Hpc Analyst job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, 3% Contract, and 1% Nights. Highlights an 93% Physical, 3% Hybrid, and 4% Remote job distribution.

Senior Systems Software Engineer - GPU Performance at Scale

OR • On-site, Remote

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees

Full-time

Re-posted 20 days ago


Key responsibilities

  • Lead the implementation of performance practices in large-scale GPU infrastructure, delivering tools, methodologies, and workflows to validate and improve datacenter products.

  • Develop engineering solutions to provide continuous insights into the performance of AI workloads and decompose complex performance or stability issues to identify root causes.

  • Analyze, debug, and resolve critical firmware and software issues to optimize AI workload performance at scale.


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology-and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing.

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.

Come join the team and see how you can make a lasting impact on the world. We are looking for a dedicated engineer for the Senior Systems Software Engineer role, focusing on GPU Performance at Scale. At NVIDIA, this role is uniquely positioned to drive innovation in AI and GPU computing.

You will contribute to world-class computing hardware and software, fueling groundbreaking advancements in artificial intelligence. You will provide insights on large-scale system composition and tuning mechanisms for high-performance compute runs. Collaborate with researchers, developers, and customers to craft improved workflows and develop new, leading solutions.

Engage with HPC, OS, CPU, GPU compute, and systems specialists to architect, build, and optimize large-scale performance platforms. What you'll be doing: Lead the implementation of performance practices in large-scale GPU infrastructure, delivering powerful tools, methodologies, and flows to validate and improve multiple datacenter products concurrently. Align next-generation AI workloads with next-generation datacenter builds for NVIDIA GPUs, CPUs, and networking hardware.

Engage early with HW/FW/SW/platform internal and customer teams. Develop engineering solutions that provide continuous insights into the performance of AI workloads in evolving environments, generating swift insights into improvements and regressions. Decompose high-complexity performance or stability issues into minimal reproduction cases, working towards identifying the root cause.

Participate in collaborations with various SW and FW teams (BMC/SBIOS/OS/drivers, etc.) to develop outstanding methods and tools. Analyze, debug, and resolve critical firmware and software issues to achieve the highest AI workload performance at scale. What we need to see: Proven understanding of accelerated computing software stacks (CUDA)

Experience with modern cloud and container-based enterprise computing architectures, with Slurm preferred. Strong programming and scripting experience in C/C++/Python/Bash. Deep expertise in systems architecture and the impact of various components on performance.

Experience with container technology and Linux-based OSes, with Docker preferred. Experience supporting high-performance computing or deep learning in engineering or academic research communities. Strong teamwork and communication skills, coupled with results-focused analytical abilities.

BS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience); MS or PhD desirable with 8+ years of applicable experience. Ways to Stand Out From the Crowd End-to-end GPU performance engineering from the profiler to systems analysis. Linux systems programming and optimization experience.

Exposure to virtualization techniques and cloud platform solutions. Experience with scheduling and resource management systems. Experience with large-scale HPC environments.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 9, 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.


What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US