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

Contemporaries

Data Engineer

Durham, NC · On-site

$57 - $63/hr

... Data Engineer to support environmental health and extreme weather research initiatives. This ... Create documentation and best practices related to GPU resource allocation and performance ...

Nvidia

EDA Workflow Optimization Engineer

Durham, NC · Hybrid

$107K - $127K/yr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... You will continuously innovate and enhance scalable, reliable, high performance systems and tools ...

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 ...

Nvidia

Senior Developer Technology Engineer - AI

Durham, NC · Hybrid

$52.75 - $69.50/hr

... Engineer, Artificial Intelligence! Would you enjoy researching parallel algorithms to accelerate AI ... low-level performance optimizations. * In-depth expertise with CPU and GPU architecture ...

Nvidia

Senior System Simulation Architect

Durham, NC · On-site

... GPU) workloads - with special focus on the CPU subsystem. * Integrate functional models from ... Support CPU architects and performance engineers in their use of functional models, performance ...

AGBO

Technical Artist, Environment

Raleigh, NC · On-site

$123K - $147K/yr

... and Engineering teams. You will drive the environment art pipeline from asset ingestion to in ... Ability to read and communicate GPU performance data clearly Additional Information: This role is ...

Epic Games

Principal VFX Artist

Cary, NC · On-site

Collaborate with Tech Art and Engineering to define performance budgets and hit them without ... Strong understanding of GPU performance - draw calls, particle costs, memory - and a track record ...

AGBO

Technical Artist, Environment

Raleigh, NC

$123K - $147K/yr

... and Engineering teams. You will drive the environment art pipeline from asset ingestion to in ... Ability to read and communicate GPU performance data clearly Additional Information: This role is ...

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Gpu Performance Engineer information

See Raleigh, NC salary details

$10

$58

$95

How much do gpu performance engineer jobs pay per hour?

As of Jul 13, 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
Software Engineer - AI Research Clusters

Software Engineer - AI Research Clusters

Nvidia

Durham, NC • On-site

Full-time

Posted 7 days ago

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies

Job description

NVIDIA is at the forefront of innovations in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention-the GPU-functions as the visual cortex of modern computing and is central to groundbreaking applications from generative AI to autonomous vehicles. We are now looking for a Software Engineer to help accelerate the next era of machine learning innovation.

In this role, you will propose and implement engineering solutions to ensure delivery of functional, reliable, secure, and performance-optimal GPU clusters to internal researchers, enable them to focus on training and development by reducing operational disruption and overhead, empower them for self-service continuous improvement on reliability, operational excellence & performance. Your work will empower scientists and engineers to train, fine-tune, and deploy the most advanced ML models on some of the world's most powerful GPU systems.

What You'll Be Doing:

  • In this position, you will work with coworkers across the AI Platform organization to understand the pain points of validating, monitoring and operating GPU clusters at scale. Then you will design, develop and maintain engineering solutions to solve those pain points systematically.

  • You will also research in traditional AIOps and the emerging Agentic AI, and leverage it to further reduce the operation toil.

  • You will participate in on-call support for systems, platforms built and owned by the team.

What We Need To See:

  • BS/MS in Computer Science, Engineering, or equivalent experience.

  • 2+ years in software/platform engineering, including 1 year in ML infrastructure or distributed systems.

  • Experience in software development lifecycle on Linux-based platforms.

  • Strong coding skills in languages such as Python, C++ or Rust.

  • Experience with Docker, Kubernetes, GitLab CI, automated deployments.

  • Experience with AIOps or Agentic AI and apply it successfully in production environment.

Ways To Stand Out From The Crowd:

  • Proficiency with full-stack development: Relational Data Modeling, DB optimization, REST API Semantics, Javascript, CSS, providing API as a service.

  • Passion for building developer-centric platforms with great UX and strong operational reliability.

  • Experience running Slurm or custom scheduling frameworks in production ML environments.

  • Familiarity with GPU computing, Linux systems internals, and performance tuning at scale.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 10, 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

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

Year founded

1993

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