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Gpu Jobs (NOW HIRING)

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 ...

Nvidia

Senior GPU Architect

Santa Clara, CA · On-site

$152K - $206K/yr

NVIDIA's GPU Architecture Group is looking for architects to contribute to the design of our proprietary profiler subsystem, the apparatus embedded in every GPU that enables our profiling and ...

Nvidia Corporation

Senior GPU Architect

Santa Clara, CA · On-site

$152K - $206K/yr

NVIDIA's GPU Architecture Group is looking for architects to contribute to the design of our proprietary profiler subsystem, the apparatus embedded in every GPU that enables our profiling and ...

Nvidia

$129K - $176K/yr

NVIDIA's GPU Architecture Group is looking for architects to contribute to the design of our proprietary profiler subsystem, the apparatus embedded in every GPU that enables our profiling and ...

Apple

GPU Power Efficiency Engineer

Austin, TX · On-site

As a member of the Silicon Technologies GPU team, you will work across functions including Architecture, Power, Performance, Silicon Validation, Thermals and Technology. The job involves analyzing ...

Apple

GPU Benchmark Analysis Architect

Cupertino, CA · On-site

$206K/yr

Analyze GPU workloads performance and bottlenecks various devices. Implement and/or suggest improvements to remove the identified bottlenecks.Build targeted microbenchmarks to help understand ...

MediaTek

Sr. GPU Compiler Developer

San Diego, CA · On-site

$57.75 - $76.50/hr

The role involves developing and implementing GPU compiler pipelines and analyzing code generation issues. Responsibilities : • Define GPU compiler software architecture and interfaces. • ...

Apple

GPU Performance Modeling Engineer

San Diego, CA · On-site

As a GPU performance modeling engineer, you will be responsible for developing cycle-approximate perf C/C++ models in close collaboration with architects and designers. Additionally, you will analyze ...

Qualcomm

GPU Compiler Engineer

San Diego, CA · On-site

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation ...

Qualcomm

GPU Performance Engineer

San Diego, CA · On-site

$87K - $116K/yr

Engineering Group, Engineering Group > GPU ASICS Engineering General Summary: As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation ...

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How much do gpu jobs pay per hour?

As of Jun 20, 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 jobs pay $500,000 a year in the US?

High-paying jobs related to GPU technology typically include senior roles such as GPU architects, machine learning engineers, and graphics hardware directors, often requiring advanced degrees and extensive experience. These positions may involve leadership, research, or specialized technical skills and are usually found in large tech companies or research institutions. Compensation at this level often includes base salary, bonuses, and stock options, but such roles are highly competitive and rare.

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.

What jobs pay $400 an hour?

High-paying jobs related to GPU work typically include specialized roles such as AI research scientists, machine learning engineers, and graphics software developers, especially those with advanced skills and experience. These positions often require advanced degrees, expertise in programming, and experience with GPU hardware and parallel computing. Such roles are usually found in technology companies, research institutions, or consulting firms and may involve consulting or freelance work for high hourly rates.

What is a GPU job?

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 engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or systems architecture can earn $500,000 or more annually, especially with experience, advanced skills, and working in high-demand industries or companies. Executive or leadership roles like engineering managers or CTOs also often reach this compensation level, often including bonuses and stock options.

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

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 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 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.

Which 3 jobs will survive AI?

GPU-related roles such as hardware engineers, AI/ML specialists, and data scientists are likely to persist as they require specialized technical skills and understanding of complex systems. These jobs involve designing, developing, and maintaining AI infrastructure, which AI itself cannot fully automate. Continuous learning and expertise in programming, algorithms, and hardware are essential for these roles to remain relevant.
More about Gpu jobs
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What are the most commonly searched types of Gpu jobs? The most popular types of Gpu jobs are:
What states have the most Gpu jobs? States with the most job openings for Gpu jobs include:
What job categories do people searching Gpu jobs look for? The top searched job categories for Gpu jobs are:
Gpu jobs near you
Infographic showing various Gpu job openings in the United States as of June 2026, with employment types broken down into 98% Full Time, 1% Part Time, and 1% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution, with an average salary of $114,281 per year, or $54.9 per hour.

GPU Performance Engineer

Genmo

San Francisco, CA • On-site

Full-time

Posted 16 days ago

Job description

We are Genmo, a research lab dedicated to building open, state-of-the-art models for video generation towards unlocking the right brain of AGI. Join us in shaping the future of AI and pushing the boundaries of what's possible in video generation.
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 optimization expert, using advanced profiling tools to identify bottlenecks and implementing solutions that achieve 5-10x speedups. From writing custom CUDA kernels to eliminating cold start latency, you'll ensure our infrastructure delivers world-class performance. This role is perfect for someone who gets excited about microsecond optimizations and pushing hardware to its theoretical limits.
Key Responsibilities
  • Profile and optimize GPU workloads using Nsight Systems, nvprof, and custom instrumentation
  • Write high-performance CUDA and Triton kernels for critical model operations
  • Optimize cold start latency from seconds to milliseconds for our serving infrastructure
  • Tune memory access patterns, kernel fusion, and GPU utilization
  • Collaborate with ML engineers to optimize model implementations
  • Debug performance issues across the full stack from application to hardware
  • Implement custom memory pooling and allocation strategies
  • Share optimization techniques and build performance culture across teams

Qualifications
  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
  • 5+ years systems programming experience with 3+ years focused on GPU optimization
  • Expert proficiency with GPU profiling tools (Nsight Systems, nvprof)
  • Strong CUDA programming skills with production kernel development
  • Deep understanding of GPU architecture (memory hierarchy, SMs, warps)
  • Track record of achieving significant performance improvements (5-10x)
  • Experience with Python and C++ in production environments

We Value
  • Experience with Triton kernel development
  • Knowledge of CUTLASS or similar high-performance libraries
  • Background in ML-specific optimizations (attention, transformers)
  • RDMA/InfiniBand optimization experience
  • Contributions to GPU libraries or frameworks
  • Low-level debugging skills (PTX/SASS reading)

Genmo is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law. Genmo, Inc. is an E-Verify company and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish.

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