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Gpu Profiling Engineer Jobs (NOW HIRING)

YO AI Labs

CUDA Software Engineer - Remote

Chicago, IL · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Analyze, profile, and optimize GPU kernels using CUDA and profiling tools. * Identify performance ...

YO AI Labs

CUDA Engineering Expert - Remote

Houston, TX · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Analyze, profile, and optimize GPU kernels using CUDA and profiling tools. * Identify performance ...

YO AI Labs

CUDA Software Engineer - Remote

Boston, MA · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Analyze, profile, and optimize GPU kernels using CUDA and profiling tools. * Identify performance ...

YO AI Labs

CUDA Software Engineer - Remote

Boston, MA · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Analyze, profile, and optimize GPU kernels using CUDA and profiling tools. * Identify performance ...

YO AI Labs

CUDA Software Engineer - Remote

Austin, TX · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Analyze, profile, and optimize GPU kernels using CUDA and profiling tools. * Identify performance ...

YO AI Labs

CUDA Software Engineer - Remote

Dallas, TX · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Analyze, profile, and optimize GPU kernels using CUDA and profiling tools. * Identify performance ...

YO AI Labs

CUDA Software Engineer - Remote

San Jose, CA · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Analyze, profile, and optimize GPU kernels using CUDA and profiling tools. * Identify performance ...

YO AI Labs

CUDA Software Engineer - Remote

Seattle, WA · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Analyze, profile, and optimize GPU kernels using CUDA and profiling tools. * Identify performance ...

YO AI Labs

CUDA Software Engineer - Remote

New York, NY · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Analyze, profile, and optimize GPU kernels using CUDA and profiling tools. * Identify performance ...

YO AI Labs

CUDA Software Engineer - Remote

Palo Alto, CA · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Analyze, profile, and optimize GPU kernels using CUDA and profiling tools. * Identify performance ...

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Showing results 21-40

All JobsGpu Profiling Engineer Jobs

Gpu Profiling Engineer information

See salary details

$52.5K

$108.8K

$149K

How much do gpu profiling engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for gpu profiling engineer in the United States is $108,775.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,500.00 and $131,500.00 per year, depending on experience, location, and employer.

What does a GPU Profiling Engineer do?

A GPU Profiling Engineer specializes in analyzing and optimizing the performance of graphics processing units (GPUs) in software and hardware systems. They use profiling tools to monitor GPU utilization, identify bottlenecks, and recommend improvements to boost efficiency and speed. Their work is critical in industries like gaming, AI, and scientific computing, where high GPU performance is essential. Typically, they collaborate with software developers and hardware engineers, ensuring applications make the most effective use of GPU resources.

What are the key skills and qualifications needed to thrive as a GPU Profiling Engineer?

To thrive as a GPU Profiling Engineer, you need a strong background in computer science, graphics programming, and performance analysis, usually supported by a relevant degree. Proficiency with profiling tools like NVIDIA Nsight, AMD Radeon GPU Profiler, and familiarity with graphics APIs such as Vulkan or DirectX is typically required. Analytical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and collaborating with development teams. These competencies ensure efficient GPU performance optimization, enabling high-quality graphics and smooth application experiences.

What are some typical challenges faced by a GPU Profiling Engineer when optimizing application performance?

GPU Profiling Engineers often encounter challenges such as identifying performance bottlenecks caused by inefficient memory access patterns, thread divergence, or suboptimal kernel usage. Analyzing complex profiling data and translating it into actionable optimization steps requires a deep understanding of both hardware and software. Additionally, collaborating closely with development and QA teams to test and refine optimizations is a critical part of the role, as changes can have wide-ranging impacts on application stability and speed.

What are popular job titles related to Gpu Profiling Engineer jobs?

For Gpu Profiling Engineer jobs, the most frequently searched job titles are:

Infographic showing various Gpu Profiling Engineer job openings in the United States as of August 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $108,775 per year, or $52.3 per hour.

Principal Software Engineer, Profiling Services

Santa Clara, CA • On-site

NVIDIA Corporation
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about NVIDIA Corporationexternal

$157K - $210K/yr

Other

Re-posted 26 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

Job description

Help design and ship an Always-On, low-overhead GPU profiling service that runs in production, scales across cluster environments, and delivers actionable insights for ML workloads. You will lead the architecture and hands-on delivery across system software, drivers, and CUDA to make profiling continuously available and reliable.
What you'll be doing:
  • Design the architecture for an Always-On profiling service, defining interfaces, data flows, and scalability guarantees for multi-process/GPU/node systems.
  • Drive low-overhead, high-reliability implementations in C/C++, including IPC/shared memory, and bounded CPU/memory budgets.
  • Lead end-to-end feature delivery spanning user-mode components, driver/platform layers, and performance counter/trace providers.
  • Establish profiling models that integrate with existing ML/AI workflows (e.g., PyTorch/XLA) to turn low-level signals into actionable insights.
  • Set technical direction for an engineering team; mentor engineers, drive technical planning to mitigate architectural risks, and align roadmaps across internal and external partners.
What we need to see:
  • BS or MS degree or equivalent experience in Computer Engineering, Computer Science, or related degree.
  • 15+ years of system-level C/C++ development, including concurrency, memory management, and performance engineering.
  • Proven experience designing and shipping production quality system software or drivers with strict reliability, observability, and performance constraints.
  • Demonstrated technical leadership: defining architecture and success metrics, and translating abstract product visions into actionable technical roadmaps with fast-paced, multidisciplinary teams.
  • Strong interpersonal, verbal, and written communication; able to influence across organizations and build trust with external collaborators.
Ways to stand out from the crowd:
  • Extensive experience with profiling/tracing stacks for CPU/GPU (e.g., CUPTI, Nsight, performance counters, event correlation) and debugging highly concurrent systems.
  • Deep hands-on knowledge of CUDA and GPU architecture, including runtime/driver APIs, CUDA streams/graphs, and kernel behavior.
  • Track record building continuous, always-on, or multi-client profiling systems designed for predictable overhead at scale.
  • Hands-on experience tuning ML training/inference loops based on deep profiling analysis, with familiarity in ML ecosystems (e.g., PyTorch, JAX) and correlating application events with GPU metrics to translate data into actionable performance insights (e.g., bottleneck triage, compute vs. memory bound).
  • Experience with user-mode driver development and integration within platform security and permissions models.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until February 14, 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.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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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

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