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Gpu Performance Engineer Jobs in Raleigh, NC (NOW HIRING)

Nvidia

Senior GPU Memory Architect

Durham, NC

... programmable GPUs and the CUDA language and is a world leader in high-performance computing ... Develop architecture and micro-architecture features to improve the state-of-the-art in GPU memory ...

SAS

DevOps Engineer

Cary, NC · On-site

$49.25 - $67.50/hr

Maintain GPU-based infrastructure including optimizing GPU utilization for largescale deep learning ... Work closely with data scientists to resolve performance bottlenecks and infrastructure issues.

SAS

DevOps Engineer

Cary, NC · On-site

$49.25 - $67.50/hr

Maintain GPU-based infrastructure including optimizing GPU utilization for large-scale deep ... Work closely with data scientists to resolve performance bottlenecks and infrastructure issues.

Nvidia

Senior ML Platform Engineer

Durham, NC

$101K - $138K/yr

... Performance Computing, and Visualization. Our invention-the GPU-functions as the visual cortex of ... We are now looking for a ML Platform Engineer to help accelerate the next era of machine learning ...

NVIDIA

Senior ML Platform Engineer

Durham, NC · On-site

$101K - $138K/yr

... GPU clusters. • Apply SRE principles to diagnose, troubleshoot, and resolve complex system issues across the entire stack, ensuring high availability and performance for critical AI workloads. • ...

Nvidia

Senior ASIC Power Engineer

Durham, NC

Develop innovative HW, GPU and system designs to extend the state of the art performance and ... or MS in electrical engineering or computer science or equivalent experience * 5+ years of ...

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Gpu Performance Engineer information

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How much do gpu performance engineer jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for gpu performance engineer in Raleigh, NC is $58.43, according to ZipRecruiter salary data. Most workers in this role earn between $47.88 and $66.11 per hour, depending on experience, location, and employer.

What are some common challenges faced by GPU Performance Engineers when optimizing graphics workloads?

GPU Performance Engineers often encounter challenges such as identifying performance bottlenecks within complex graphics pipelines, balancing resource utilization, and achieving optimal frame rates across diverse hardware configurations. They must use specialized profiling tools and collaborate closely with developers, driver engineers, and QA teams to address issues like memory bandwidth limitations or shader inefficiencies. Staying updated with rapidly evolving GPU architectures and optimizing for both current and next-generation hardware are also key aspects of the role.

What is a GPU Performance Engineer?

A GPU Performance Engineer is a specialist who analyzes, optimizes, and improves the performance of graphics processing units (GPUs). They work on identifying bottlenecks, optimizing code, and ensuring that GPU hardware and software deliver maximum efficiency and speed. Their role may involve working with drivers, firmware, and applications to enhance graphics and compute workloads. This job is essential in industries like gaming, AI, and high-performance computing where GPU efficiency directly impacts user experience and system performance.

What are the key skills and qualifications needed to thrive as a GPU Performance Engineer, and why are they important?

To thrive as a GPU Performance Engineer, you need a strong background in computer architecture, programming (C/C++), and a degree in computer science, electrical engineering, or a related field. Proficiency with GPU profiling tools (e.g., NVIDIA Nsight, AMD Radeon GPU Profiler), performance analysis frameworks, and parallel computing libraries like CUDA or OpenCL is typically required. Analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for collaborating with developers and debugging performance bottlenecks. These skills and qualities are essential for optimizing GPU performance, ensuring efficient software-hardware interaction, and delivering high-quality graphics or compute solutions.

What is the difference between Gpu Performance Engineer vs Gpu Hardware Engineer?

AspectGpu Performance EngineerGpu Hardware Engineer
Primary FocusOptimizing GPU performance, benchmarking, and tuning softwareDesigning, developing, and testing GPU hardware components
Required SkillsProgramming, performance analysis, GPU architecture knowledgeHardware design, circuit analysis, FPGA/ASIC experience
Work EnvironmentSoftware development teams, labs for testing performanceHardware labs, manufacturing facilities, R&D centers
Common CertificationsNone specific, often requires computer engineering or related degreesElectrical engineering, VLSI design certifications

The Gpu Performance Engineer primarily focuses on optimizing and testing GPU software performance, while the Gpu Hardware Engineer designs and develops the physical GPU components. Both roles require a strong background in computer engineering, but differ in their core responsibilities and work environments.

What are popular job titles related to Gpu Performance Engineer jobs in Raleigh, NC? For Gpu Performance Engineer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Gpu Performance Engineer jobs in Raleigh, NC look for? The top searched job categories for Gpu Performance Engineer jobs in Raleigh, NC are:
Gpu Performance Engineer jobs near you
Senior GPU Memory Architect

Senior GPU Memory Architect

Nvidia

Durham, NC

Full-time

Posted 10 days ago

Job description

NVIDIA is seeking a world-class computer architect to contribute to the development of future high-performance computing systems, with a focus on enhancing the power-constrained performance of the hardware. Ideal candidates will have a strong track record of understanding and analyzing memory systems architecture to improve performance per watt (perf/W) and performance per millimeter (perf/mm). A broad perspective across the field of computer architecture and depth in the area of power, performance, and area (PPA) analysis is highly desirable. NVIDIA has pioneered programmable GPUs and the CUDA language and is a world leader in high-performance computing technology, with aggressive plans for future processors. This position offers the opportunity to have a real impact in a fast-moving, technology-focused company.

What you will be doing:

  • Develop innovative high-performance processor and system architectures, focusing on the memory system and energy efficiency.

  • Develop architecture and micro-architecture features to improve the state-of-the-art in GPU memory systems, optimizing along the axes of perf/W, perf/mm, and perf/$.

  • Develop and enhance architecture prototype models for power and noise analysis.

  • Participate in performance and power simulation of features to analyze, define, and improve energy per byte.

  • Analyze benchmarks, application workloads, and performance/power simulation and emulation results to identify areas for architecture optimizations.

  • Debug power, performance, and functional issues with high-level models, RTL simulation and emulation, silicon, and systems.

  • Collaborate with outside partners on system infrastructure.

What we want to see:

  • 10+ yrs of experience in CPU/GPU architecture, memory systems design with a focus on energy efficiency in the system.

  • Bachelors in Electrical Engineering, Computer Science, or related field (or equivalent experience).

  • Expertise in power analysis and modeling in pipeline-based architectures.

  • Good understanding of power analysis tools like Ansys Power Artist, Synopsys PTPX, etc.

  • Experience with C, C++, and some scripting languages.

Ways to stand out from the crowd:

  • MS/PhD in Electrical Engineering, Computer Science, or related field

  • Experience with hardware design languages such as Verilog or VHDL

  • Prior experience in developing and optimizing algorithms for power efficiency

  • Demonstrated ability to innovate and drive continuous improvement in system architecture

  • Excellent communication skills, both written and verbal, for effective collaboration with internal teams and external partners.

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 March 3, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.
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

Year founded

1993

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