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Gpu Performance Engineer Jobs (NOW HIRING)

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 ...

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 ...

We are looking for passionate GPU performance modeling engineers that will help shape the architecture of future Adreno GPUs for Qualcomm Snapdragon compute platforms across smartphones, Windows PCs ...

GPU Performance Engineer

San Diego, CA ยท On-site

$87K - $116K/yr

As a Qualcomm GPU Engineer, you may architect, design, implement, verify, and/or optimize the performance and power of GPU cores. Qualcomm Engineers collaborate with cross-functional teams to meet ...

Performance Engineer, GPU

San Francisco, CA ยท On-site

$280K - $850K/yr

As a GPU Performance Engineer, you'll architect and implement the foundational systems that power Claude and push the frontiers of what's possible with large language models. You'll be responsible ...

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 ...

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 ...

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How much do gpu performance engineer jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for gpu performance engineer in the United States is $60.11, according to ZipRecruiter salary data. Most workers in this role earn between $49.28 and $68.03 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.

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What states have the most Gpu Performance Engineer jobs? States with the most job openings for Gpu Performance Engineer jobs include:
What job categories do people searching Gpu Performance Engineer jobs look for? The top searched job categories for Gpu Performance Engineer jobs are:

GPU Performance Engineer

Genmo

San Francisco, CA โ€ข On-site

Full-time

Posted 6 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.