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Gpu Performance Engineer Jobs in Wisconsin (NOW HIRING)

ConfigUSA

CUDA Programmer

Waukesha, WI · On-site

Profile and tune GPU applications for performance, memory efficiency, and scalability. * Work with CPU-GPU parallel programming models and optimize data transfer. * Leverage NVIDIA libraries (CUDA ...

Serve Robotics

$225K - $260K/yr

... performance autonomy models. By optimizing distributed training pipelines, neural network ... This includes ensuring data is efficiently loaded, distributed, and processed across large GPU ...

Gehc

Senior Software Engineer

Waukesha, WI

$122.60K - $161.70K/yr

Facilitate performance issues triage and resolution when spanning hardware, firmware and operating ... Experience with GPU, Drivers, BIOS, Networking, GPU technologies. * Demonstrated expertise in Linux ...

GE HealthCare

Senior Software Engineer

Waukesha, WI · On-site

$122.60K - $161.70K/yr

Facilitate performance issues triage and resolution when spanning hardware, firmware and operating ... Experience with GPU, Drivers, BIOS, Networking, GPU technologies. * Demonstrated expertise in Linux ...

LRS

Software Engineer, Intern

Waukesha, WI

$23.50/hr

You'll contribute to algorithm development and highperformance computing (GPU/CPU) on Linux, with a ... Explore and evaluate emerging HPC technologies to optimize MR performance. Collaborate with ...

LRS

Software Engineer

Waukesha, WI · On-site

$35 - $45/hr

... efficiency and performance Collaborate with crossfunctional teams to translate CT image ... GPU computing technologies (such as CUDA or OpenCL) Familiarity with Python and Linux shell ...

LRS

Software Engineer Internship

Waukesha, WI

$23.50/hr

This internship offers hands-on experience with high-performance computing technologies, helping to ... Experience with C++, Linux OS Experience with GPU Processing (for ex. CUDA ) Strong analytical and ...

LRS

Junior Software Engineer Intern

Brookfield, WI

$23.50/hr

... to support performance improvements Collaborate with crossfunctional teams to translate ... GPU programming technologies such as CUDA and/or OpenCL Familiarity with scripting languages such ...

GE HealthCare

Senior Software Engineer

Waukesha, WI · On-site

$122.60K - $161.70K/yr

Facilitate system performance issue triage and resolution. * Research industry trends in Compute ... Experience with Virtualization, Device Drivers, BIOS, Networking, and GPU technologies. * Automated ...

Gehc

Senior Software Engineer

Waukesha, WI

$122.60K - $161.70K/yr

Facilitate system performance issue triage and resolution. * Research industry trends in Compute ... Experience with Virtualization, Device Drivers, BIOS, Networking, and GPU technologies. * Automated ...

Deloitte

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$102.70K - $141K/yr

... performance data architecture solutions that supports both the client business as well as AI/GenAI ... SysOps Administrator, DevOps Engineer, Solutions Architect) • 2+ years of experience with GPU ...

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Gpu Performance Engineer information

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 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 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 Wisconsin? For Gpu Performance Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Gpu Performance Engineer jobs in Wisconsin look for? The top searched job categories for Gpu Performance Engineer jobs in Wisconsin are:
What cities in Wisconsin are hiring for Gpu Performance Engineer jobs? Cities in Wisconsin with the most Gpu Performance Engineer job openings:
Gpu Performance Engineer jobs near you

CUDA Programmer

ConfigUSA

Waukesha, WI • On-site

Contractor

Posted 2 days ago

Job description

CUDA Programmer
Location: Waukesha, WI

We are seeking a skilled CUDA Programmer to design, develop, and optimize high-performance applications on NVIDIA GPUs. The role focuses on accelerating compute-intensive workloads, optimizing memory usage, and collaborating with system and application teams to maximize GPU performance.

Key Responsibilities

  • Profile and tune GPU applications for performance, memory efficiency, and scalability.
  • Work with CPU–GPU parallel programming models and optimize data transfer.
  • Leverage NVIDIA libraries (CUDA, cuBLAS, cuDNN, NCCL as applicable).
  • Collaborate with system, compute, or AI/ML teams to integrate GPU-accelerated components.
  • Debug GPU kernels and address performance bottlenecks using NVIDIA profiling tools.
  • Ensure portability and performance across different NVIDIA GPU architectures.

Required Skills

  • Strong experience in CUDA programming and parallel computing concepts.
  • In-depth understanding of NVIDIA GPU architecture (threads, warps, SMs, memory hierarchy).
  • Proficiency in C/C++ for high-performance computing.
  • Experience with CUDA profiling and debugging tools (Nsight, nvprof).
  • Solid understanding of multi-threading, memory optimization, and performance tuning.

Preferred Skills

  • Experience with AI/ML, HPC, or graphics workloads on GPUs.
  • Familiarity with multi-GPU programming and communication frameworks (NCCL, MPI).
  • Exposure to Python bindings (CUDA Python, PyTorch extensions).
  • Experience with Linux-based development environments.