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Gpu Performance Engineer Jobs in Wisconsin (NOW HIRING)

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 · On-site

$122K - $161K/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

$122K - $161K/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 ...

Nscale

WI · On-site

$77.39 - $103.19/hr

Infrastructure Operations Engineer (Narvik) Norway About Nscale Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large ...

NVIDIA Gruppe

WI · On-site

$168 - $334/hr

... production GPU and Kubernetes environments to ensure high availability and performance. Apply ... Engineering, Physics, Mathematics, or equivalent experience. * Expert‑level Linux system ...

NVIDIA Corporation

WI · On-site

$200 - $391/hr

We build and manage the automation ecosystem supporting NVIDIA's GPU Cloud and NVIDIA SuperPod ... performance computing management solutions.Be a proactive problem solver, looking out for new ...

GE HealthCare

Software Engineer

Waukesha, WI · On-site

This work requires balancing image quality, computational performance, radiation dose, and the ... Familiarity with GPU technologies; CUDA or OpenCL Desired Characteristics We are seeking engineers ...

Gehc

Software Engineer

Waukesha, WI · On-site

This work requires balancing image quality, computational performance, radiation dose, and the ... Familiarity with GPU technologies; CUDA or OpenCL Desired Characteristics We are seeking engineers ...

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 ...

GE HealthCare

Senior Software Engineer

Waukesha, WI · On-site

$122K - $161K/yr

... performance issue triage and resolution. • Research industry trends in Compute, containers ... GPU technologies. • Automated testing experience test case development, maintenance, and ...

Nscale

WI · On-site

$82.55 - $123.83/hr

Note to candidates: this role is based out of Sauda, Rogaland About Nscale Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and ...

Accenture

AI & HPC Infrastructure Engineer

Milwaukee, WI · On-site

$105K - $138K/yr

... performance, scalability, resiliency, and governance needs * Deploy, configure, and manage XPU-based clusters (GPU, DPU, LPU, CPU) across bare-metal and containerized environments using workload ...

Jobtailor

WI · On-site

$120 - $190/hr

Define and deliver high-value, GPU-accelerated AI solutions for energy operations that meet these ... Implement predictive asset maintenance and asset-performance management solutions. * Deploy real ...

VITO Research

WI · On-site

$100 - $130/hr

Monitor performance, troubleshoot issues, and ensure reliability of delivered analytics products ... Background supporting ML/AI teams, GPU workloads, or high‑performance compute environments. What ...

GE HealthCare

Senior Software Engineer

Waukesha, WI · On-site

$122K - $161K/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 · On-site

$122K - $161K/yr

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

Cirrascale Corporation

WI · On-site

$145 - $175/hr

Cirrascale Cloud Services provides high-performance cloud infrastructure purpose-built for deep ... We specialize in dedicated GPU cloud solutions tailored to the unique needs of startups, research ...

NVIDIA Corporation

WI · On-site

$184 - $287.50/hr

... factory performance, from hardware to workload.**What You Will be Doing:*** Run AI factory ... Background in HPC systems engineering, SRE, or systems analysis for GPU-accelerated environments.

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Gpu Performance Engineer information

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 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 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 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

Lead Machine Learning Engineer

Serve Robotics

On-site, Remote

$225K - $260K/yr

Full-time

Re-posted 27 days ago

Job description

At Serve Robotics, we're reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It's designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.
The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We're looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.
Who We Are
We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.
This role develops and scales large-scale machine learning training systems for multimodal robotics data, enabling the creation of high-performance autonomy models. By optimizing distributed training pipelines, neural network architectures, and data processing workflows, the position improves training efficiency, accelerates model iteration, and maximizes GPU utilization. The role collaborates closely with ML researchers and infrastructure teams, influencing the design, deployment, and performance of end-to-end autonomy models and the large-scale data pipelines that support them.
Responsibilities
  • Design and maintain training systems that can process and learn from petabyte-scale multimodal datasets (e.g., video and point cloud data). This includes ensuring data is efficiently loaded, distributed, and processed across large GPU clusters.
  • Identify and resolve bottlenecks in the training pipeline, including data loading, preprocessing, model computation, and inter-node communication, to maximize GPU utilization and reduce training time.
  • Work with the ML team to develop and refine neural network architectures suitable for autonomy tasks, particularly those handling high-dimensional and sequential sensor data.
  • Create and adjust loss functions and training strategies that help the model learn effectively from complex multimodal inputs and improve autonomy performance.
  • Configure, monitor, and maintain large-scale distributed training jobs across multiple machines and GPUs, ensuring stability, fault tolerance, and efficient resource usage.
  • Implement scalable systems to preprocess, transform, and augment large robotics datasets so that they are suitable for model training.
  • Work closely with ML scientists and other engineers to integrate new models, experiments, and training approaches into the production training pipeline.
  • Analyze training metrics, model outputs, and experiment logs to assess model performance and guide improvements in architecture, data usage, or training strategies.
  • Develop tools and workflows that allow teams to run experiments, track results, and iterate quickly on new model ideas or training approaches.

Qualifications
  • Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline.
  • Minimum of 5 years of professional experience developing, training, and deploying machine learning models in production environments.
  • Hands-on experience training machine learning models across multiple GPUs or compute nodes, including familiarity with distributed training frameworks and large dataset handling.
  • Strong programming skills in Python for implementing machine learning models, data pipelines, and training workflows.
  • Solid knowledge of core concepts such as neural networks, optimization algorithms, loss functions, model evaluation, and training methodologies.

What Makes You Stand out
  • Experience identifying and resolving training bottlenecks related to compute utilization, memory usage, and data throughput in machine learning systems.
  • Experience training machine learning models on robotics or autonomous driving datasets involving multimodal sensor inputs such as camera video, LiDAR point clouds, radar, or telemetry data.
  • Experience developing models that combine multiple data modalities (e.g., images, point clouds, and structured sensor data) into a unified learning system.
  • Peer-reviewed publications or significant research contributions in machine learning, robotics, or related areas.

*Please note: The listed base salary range applies to candidates based in the US. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely in Canada
  • Canada - ALL: $177k - $215k CAD

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