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Gpu Performance Engineer Jobs in Dallas, TX (NOW HIRING)

Photon

QA Engineer (Performance)- Dallas, TX

Dallas, TX · On-site

$138K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... and GPU/compute bottlenecks. * RAG Performance Analysis: Test the speed and efficiency of the ... Experience: 8+ years in Performance Engineering, with a specific focus on AI/ML applications or ...

Photon

QA Engineer (Performance)- Dallas, TX

Dallas, TX

$138K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... and GPU/compute bottlenecks. * RAG Performance Analysis: Test the speed and efficiency of the ... Experience: 8+ years in Performance Engineering, with a specific focus on AI/ML applications or ...

4MindsAI Inc.

Machine Learning Operations Engineer

Dallas, TX · On-site

$130 - $200/hr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Solid understanding of GPU cluster management and the performance tradeoffs across hardware ... Master's degree in Computer Science, Engineering, or a related field, or equivalent practical ...

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Gpu Performance Engineer information

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How much do gpu performance engineer jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for gpu performance engineer in Dallas, TX is $59.46, according to ZipRecruiter salary data. Most workers in this role earn between $48.75 and $67.31 per hour, depending on experience, location, and employer.

What are some common challenges faced by a GPU performance engineer 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.

What are popular job titles related to Gpu Performance Engineer jobs in Dallas, TX?

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The top searched job categories for Gpu Performance Engineer jobs in Dallas, TX are:

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Cities near Dallas, TX with the most Gpu Performance Engineer job openings:

Gpu Performance Engineer jobs near you
Infographic showing various Gpu Performance Engineer job openings in Dallas, TX as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution, with an average salary of $123,673 per year, or $59.5 per hour.

HPC Performance and Validation Engineer

NorthMark Strategies

Dallas, TX • On-site

Full-time

Re-posted 17 days ago

Job description

The Company
NorthMark Compute & Cloud (NMC²) is backed by dedicated leadership and investment, with a clear mission as it operates at the bleeding edge of technology. Its goal is to scale and enhance the high-performance computing (HPC) and cloud infrastructure that supports its clients' research, production, and delivery, enabling breakthroughs that shape the industries of tomorrow. Its engineers build critical infrastructure to eliminate friction in scientific research, simulations, analysis, and decision-making, accelerating discovery and driving faster innovation.
The Position
As an HPC Validation and Performance Engineer at NMC², you will take ownership of the validation and optimization of our HPC CPU and GPU calc farms. This critical role will involve developing a validation and performance baselining framework, which ensures system readiness for AI/ML and HPC workloads across multiple architectures. Your role will be essential in providing continuous performance benchmarking, real-time observability, and long-term strategic readiness. You will drive the implementation of advanced tooling and frameworks, maintaining an infrastructure that is crucial to our cutting-edge research efforts. You will be accountable for providing data driven performance metrics to support architectural design choices as we continue to globally scale our datacenter footprint. We are looking for someone with deep technical expertise in compute, storage or networking optimizations and performance engineering who can develop solutions that scale with our growing infrastructure. This role demands a forward-thinking engineer who can anticipate industry trends and adopt emerging architectures and strategies to keep NMC² at the forefront of innovation.
Responsibilities:
  • Architecting and implementing a validation framework to certify the readiness and utilization of GPU nodes across a large, distributed HPC environment.
  • Defining methodologies to continually assess performance and optimising infrastructure across AI/ML workloads
  • Developing and executing comprehensive performance testing using industry and customer specific benchmarks, ensuring optimal performance across HPC compute, storage and networking
  • Contribute to research reports that will describe the discoveries of the benchmarking, evaluating the complete HW performance and efficiency
  • Leading efforts to debug, identify and then resolve bottlenecks in system performance
  • Building robust, scalable tools for automated validation and testing, utilising Python, Go, Kubernetes and CI/CD pipelines to streamline continuous validation and benchmarking processes
  • Implementing monitoring solutions using Prometheus, Grafana and other modern monitoring technologies to track performance metrics and real-time health of the cluster
  • Defining and implementing best practice for continuous performance validation, ensuring that the infrastructure remains reliable and efficient as new technologies emerge
  • Staying informed on industry trends and advancements to ensure long-term strategic alignment
  • Working cross-functionally with engineering, infrastructure and research teams to align validation efforts with the broader business objectives, ensuring that the platform meets evolving research demands

Requirements:
  • Accelerator performance experience, including profiling and tuning with large-scale GPU clusters
  • In-depth understanding of NVIDIA ClusterKit, Nsight and Validation Suite, MLPerf and DCGM tools for GPU and DPUs
  • Networking & Storage performance experience, including profiling and optimisation with NVIDIA ClusterKit, iPerf or equivalent across InfiniBand/RoCe network implementations
  • System benchmarking experience across Linux and familiarity with the Phronix suite or equivalent
  • Experience with HPC workloads across distributed global locations, bringing data driven performance data to compliment key architectural decisions
  • Strong proficiency in developing automation tools and micro benchmarking frameworks for validation using Python, Go, and Kubernetes in a Ubuntu Linux environment
  • Expertise with key monitoring platforms including OTEL, Prometheus, ELK and Grafana and in definition and implementing the overall observability strategy for HPC validation and performance monitoring
  • A deep understanding of emerging technologies, architectures and strategies, with the ability to assess their potential impact on infrastructure and adopt them as part of a long-term plan
  • Proven ability to lead complex technical projects, influence decisions and engage with stakeholders across technical and research teams

Apply