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Gpu Engineer Jobs (NOW HIRING)

Nvidia

We are now looking for a GPU Performance Engineer for Neural Reconstruction! NVIDIA is building the future of computer graphics, simulation, robotics, and embodied AI. Neural reconstruction and ...

KLA

Senior GPU HPC Software Architect (Milpitas)

Milpitas, CA · On-site

$147K - $200K/yr

The ideal candidate will have 10+ years in software engineering, driving technical strategy, architecture, and mentoring engineers. Expertise in C++, GPU programming, and large-scale systems is ...

Qualcomm

GPU Research Engineer

San Diego, CA · On-site

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: Qualcomm's GPU Research Team is looking for talented GPU architects to help advance state-of-the-art 3D GPU capabilities ...

Waymo

Software Engineer, GPU

Mountain View, NY · On-site

In this hybrid role, you will report to a Senior Software Engineer. You will: * Develop high-performance GPU primitives and abstractions to enable Waymo to scale its accelerator codebase across ...

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GPU Engineer information

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$39K

$101.8K

$137.5K

How much do gpu engineer jobs pay per year?

As of Jul 8, 2026, the average yearly pay for gpu engineer in the United States is $101,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What engineers make $300,000 a year?

Senior GPU engineers, especially those with extensive experience, advanced skills in graphics architecture, and expertise in programming languages like C++ and CUDA, can earn $300,000 or more annually. High-level roles in large tech companies or specialized fields such as AI and machine learning often offer compensation at this level, particularly with bonuses and stock options included.

What engineers make $200,000 a year?

Senior GPU engineers, especially those with extensive experience, advanced skills in graphics architecture, and proficiency with tools like CUDA or Vulkan, can earn $200,000 or more annually. High-level roles in large tech companies or specialized fields such as AI or data centers often offer such compensation packages.

What are the key skills and qualifications needed to thrive in the Gpu Engineer position, and why are they important?

To thrive as a GPU Engineer, you need strong knowledge of computer architecture, proficiency in C/C++, and experience with parallel programming models such as CUDA or OpenCL, along with a degree in computer science, electrical engineering, or a related field. Familiarity with debugging tools, driver development, performance profiling utilities, and hardware simulation platforms is typically required. Excellent problem-solving abilities, attention to detail, and effective teamwork and communication skills help distinguish top candidates. These skills ensure that GPU Engineers can develop high-performance solutions, efficiently troubleshoot hardware and software issues, and collaborate successfully in multidisciplinary environments.

What does a GPU engineer do?

A GPU engineer designs, develops, and optimizes graphics processing units and related hardware or software. They work on improving graphics performance, parallel processing, and computational efficiency, often using programming languages like C++ and tools such as CUDA or OpenCL. Their work supports applications in gaming, scientific computing, and machine learning.

What does a GPU Engineer do?

A GPU Engineer designs, develops, and optimizes graphics processing units (GPUs) for applications like gaming, artificial intelligence, and high-performance computing. They work on hardware architecture, driver development, and parallel computing optimizations to maximize performance. GPU Engineers collaborate with software developers, hardware designers, and researchers to improve graphics rendering, machine learning acceleration, and computational efficiency.

What engineer makes $500,000 a year?

Highly experienced GPU engineers working in top technology companies or specialized roles in graphics hardware development can earn salaries approaching or exceeding $500,000 annually, often including bonuses and stock options. Such compensation typically requires advanced skills in hardware design, software optimization, and extensive industry experience.

What are some common challenges faced by GPU Engineers, and how are they addressed?

GPU Engineers often face challenges such as optimizing code for maximum parallel efficiency, debugging complex hardware-software interactions, and keeping pace with rapidly evolving GPU architectures. Addressing these issues typically requires a combination of deep architectural understanding, use of specialized profiling and debugging tools, and ongoing collaboration with hardware, software, and QA teams. Many companies provide ongoing training and encourage knowledge sharing within engineering teams to help individuals stay current and effectively tackle new technical hurdles. Overcoming these challenges not only sharpens technical expertise but also opens doors for career growth into architect, team lead, or principal engineer roles.

More about GPU Engineer jobs
What cities are hiring for Gpu Engineer jobs? Cities with the most Gpu Engineer job openings:
What are the most commonly searched types of Gpu Engineer jobs? The most popular types of Gpu Engineer jobs are:
What states have the most Gpu Engineer jobs? States with the most job openings for Gpu Engineer jobs include:
What job categories do people searching Gpu Engineer jobs look for? The top searched job categories for Gpu Engineer jobs are:
GPU Engineer jobs near you
Infographic showing various Gpu Engineer job openings in the United States as of July 2026, with employment types broken down into 89% Full Time, and 11% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $101,752 per year, or $48.9 per hour.
GPU Programming Expert - Fully Remote | Upto $120/hr

GPU Programming Expert - Fully Remote | Upto $120/hr

Mercor

San Francisco, CA • Remote

$120/hr

Full-time

Re-posted 3 days ago

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: CUDA Engineering Expert
Type: Contract
Compensation: $80–$120/hour
Location: Remote

Role Responsibilities

  • Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization.
  • Use profiler metrics like L2 cache hit rate, L2 throughput, and occupancy to guide kernel improvements.
  • Review GPU kernel implementations to identify bottlenecks without needing extensive algorithmic background.
  • Write, modify, and reason about C++17, Python, and GPU programming code.
  • Apply CUDA, HIP, and shader programming expertise to improve performance outcomes.
  • Document optimization decisions clearly, noting when specific profiler metrics are useful.

Qualifications

Must-Have

  • Available to work at least 20 hrs/wk.
  • Fluent in core C++ features through C++17.
  • Working knowledge of Python and Git.
  • Fluent in at least one GPU programming model like CUDA, HIP, Slang, HLSL, or GLSL.
  • At least 1 year of professional or graduate-level research experience with GPUs.
  • Strong understanding of GPU profiler performance metrics for kernel optimization.
  • Ability to optimize GPU kernels without deep prior context on every algorithm.

Preferred

  • Experience with CUDA, HIP, CUDA C++ Core Libraries, inline PTX assembly, or tensor core-level optimization.
  • Experience optimizing kernels for NVIDIA Blackwell hardware.
  • Familiarity with NSight Compute.
  • Prior experience with GPU hardware organizations like NVIDIA, AMD, or Qualcomm.
  • Open-source contributions related to GPU kernel optimization.

Application Process (Takes 20–30 mins to complete)

  • Submit your resume or relevant technical background to get started.
  • Qualified applicants may be asked to complete a brief technical assessment or submit additional information.

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.