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Gpu Jobs (NOW HIRING)

Vultr

GPU Fabric Engineer

$125K - $135K/yr

Company paid Wellable subscription Join Vultr Vultr is seeking a highly skilled and experienced GPU Fabric Engineer to validate, troubleshoot, and optimize high-speed networking fabrics for GPU ...

YO AI Labs

GPU Programming Expert - Remote

Seattle, WA · Remote

$60 - $85/hr

GPU Programming Expert - Remote Job Type: Contractor Location: Remote Job Overview We are seeking experienced GPU Programmers / Software Engineers to design and optimize GPU-based tasks for AI and ...

New

Waymo

Software Engineer, GPU

Mountain View, CA · On-site

$204K - $259K/yr

Develop high-performance GPU primitives and abstractions to enable Waymo to scale its accelerator codebase across diverse GPU backends * Collaborate with Waymo's internal hardware team and external ...

Apple

GPU ML Engineer

Cupertino, CA · On-site

Apple's Compute Frameworks team in GPU, Graphics and Displays org provides a suite of high-performance data parallel algorithms for developers inside and outside of Apple for iOS, macOS and Apple TV. ...

Apple

GPU ML Engineer

Cupertino, CA · On-site

Apple's Compute Frameworks team in GPU, Graphics and Displays org provides a suite of high-performance data parallel algorithms for developers inside and outside of Apple for iOS, macOS and Apple TV. ...

Qualcomm

GPU Research Engineer

San Diego, CA · On-site

Qualcomm's GPU Research Team is looking for talented GPU architects to help advance state-of-the-art 3D GPU capabilities in Ray Tracing, Neural Rendering, Geometry Processing, and Machine Learning.

New

Baseten

Software Engineer - GPU Kernels

Manhattan, NY · On-site

This role involves designing high-performance GPU kernels and optimizing machine learning operations to enhance the performance of AI workloads. Responsibilities : • Design and implement high ...

Genmo

GPU Performance Engineer

San Francisco, CA · On-site

We're seeking a GPU Performance Engineer to squeeze every last FLOP from our H100 infrastructure and optimize our model serving stack to its absolute limits. The Role You'll be our performance ...

Inficare Technologies

GPU Solution Architect

Santa Clara, CA · On-site +1

$74 - $97.50/hr

GPU Solution Architect Location: Santa Clara, CA (Remote preferred; occasional onsite as required - additional remote locations available in WA, OR, and TX) Job Type: Contract Duration: 12 Months ...

NVIDIA Corporation

Senior GPU Architect

Santa Clara, CA · On-site

$184 - $287.50/hr

## Senior GPU ArchitectApplylocations: US, CA, Santa Clara: US, NC, Remote: US, TX, Remote: US, OR, Remote: US, AZ, Remotetime type: Full timeposted on: Posted Yesterdayjob requisition id:

Apple

GPU ML Engineer

Cupertino, CA

$150K - $277K/yr

Apple's Compute Frameworks team in GPU, Graphics and Displays org provides a suite of high-performance data parallel algorithms for developers inside and outside of Apple for iOS, macOS and Apple TV. ...

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How much do gpu jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for gpu in the United States is $54.94, according to ZipRecruiter salary data. Most workers in this role earn between $54.09 and $64.90 per hour, depending on experience, location, and employer.

What is a GPU?

A GPU, or Graphics Processing Unit, is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images and graphics for display. While originally developed for rendering graphics in video games and visual applications, GPUs are now widely used for parallel processing tasks in areas such as artificial intelligence, data science, and scientific computing. Their architecture allows them to handle thousands of operations simultaneously, making them much faster than traditional CPUs for certain workloads.

What is a GPU engineer?

A GPU job refers to a computing task that utilizes a Graphics Processing Unit (GPU) for acceleration. GPUs are specialized processors designed for parallel processing, making them ideal for tasks like machine learning, scientific simulations, and rendering. Many software applications offload intensive computations to GPUs to improve performance and efficiency. Jobs related to GPUs can involve programming, optimization, and hardware configuration in fields like AI, gaming, and data analysis.

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

To thrive as a GPU Engineer, you need a solid background in computer engineering, mathematics, and programming languages such as C++ or CUDA, often supported by a relevant degree. Familiarity with GPU architectures, parallel computing frameworks, and tools like OpenCL or Vulkan is typically required. Analytical thinking, problem-solving, and teamwork are essential soft skills for innovating and debugging complex systems. These abilities are crucial for optimizing performance, ensuring compatibility, and driving advancements in graphics and computational workloads.

What are some common challenges faced by GPU engineers when optimizing performance for various applications?

GPU engineers often encounter challenges such as balancing high computational throughput with power efficiency, ensuring compatibility across different hardware architectures, and optimizing code for parallel processing. They must also troubleshoot bottlenecks in memory bandwidth and latency that can impact performance. Collaboration with software developers and hardware architects is crucial to identify and resolve these issues, and staying updated with the latest advances in GPU technologies is essential for continued success.

What is the difference between Gpu vs Data Scientist?

AspectGpuData Scientist
Required CredentialsKnowledge of parallel computing, programming skills (CUDA, OpenCL)Degree in Computer Science, Statistics, or related fields; programming skills
Work EnvironmentHardware-focused, technical, often in R&D or engineering teamsData analysis, modeling, research in various industries
Industry UsageTech, gaming, AI, machine learningFinance, healthcare, tech, marketing

Gpu specialists focus on hardware and parallel processing for computing tasks, while data scientists analyze data to extract insights. Both roles require technical skills, but Gpu roles are more hardware-oriented, whereas data scientists focus on data analysis and modeling.

How to get into the graphics processing unit industry?

To enter the GPU industry, candidates typically need a strong background in computer engineering, electrical engineering, or computer science, with skills in programming languages like C++ and knowledge of graphics APIs such as DirectX or Vulkan. Relevant experience can be gained through internships, projects, or certifications in hardware design, GPU architecture, or related fields. Staying updated on industry developments and obtaining certifications like NVIDIA's or AMD's developer programs can also enhance job prospects.
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Gpu jobs near you
Infographic showing various Gpu job openings in the United States as of August 2026, with employment types broken down into 97% Full Time, 1% Part Time, and 2% Contract. Highlights an 79% Physical, 7% Hybrid, and 14% Remote job distribution, with an average salary of $114,281 per year, or $54.9 per hour.

GPU Programming Expert - Remote

YO AI Labs

Philadelphia, PA • Remote

$60 - $85/hr

Full-time

Posted yesterday

New

Job description

GPU Programming Expert - Remote

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced GPU Programmers / Software Engineers to design and optimize GPU-based tasks for AI and LLM applications. You will apply your expertise in GPU programming, performance optimization, and C++ development to build high-performance solutions.

Key Responsibilities

  • Design, implement, and optimize GPU software using CUDA, WebGPU, or GLSL.

  • Profile and optimize GPU kernels and shaders for performance and efficiency.

  • Develop host-side logic and GPU integrations using C++.

  • Create GPU-focused tasks and solutions for AI/LLM applications.

  • Analyze performance bottlenecks and implement optimization strategies.

Required Qualifications

  • Strong experience with GPU programming, particularly on NVIDIA GPUs.

  • Proficiency in CUDA, WebGPU, or GLSL.

  • Strong C++ programming skills.

  • Background in graphics programming, ML acceleration, scientific computing, HPC, or related GPU-focused fields.

  • Strong understanding of GPU architecture and performan