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Gpu Performance Engineer Jobs in Riverside, CA (NOW HIRING)

FieldAI

Senior Perception Engineer

Irvine, CA

$160K - $1M/yr

Continuously evaluate and improve perception performance through offline evaluation, simulation, on ... Experience with CUDA and GPU optimization is highly desirable. * Background in autonomous vehicles ...

FieldAI

Senior Perception Engineer

Irvine, CA · On-site

$160K/yr

Continuously evaluate and improve perception performance through offline evaluation, simulation, on ... Experience with CUDA and GPU optimization is highly desirable. * Background in autonomous vehicles ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112K - $154K/yr

Optimize infrastructure for performance and cost across cloud and edge. * Enforce best practices in ... Hands-on experience with GPU orchestration and auto-scaling (Karpenter, SageMaker, EKS)

Netlist

Director of Sales, Data Center

Irvine, CA · On-site

$200 - $250/hr

NLST) is a leading provider of high-performance modular memory subsystems and next-generation ... Join our world-class engineering team and be part of shaping the future of memory and storage ...

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How much do gpu performance engineer jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for gpu performance engineer in Riverside, CA is $62.71, according to ZipRecruiter salary data. Most workers in this role earn between $51.39 and $70.96 per hour, depending on experience, location, and employer.

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 Riverside, CA?

For Gpu Performance Engineer jobs in Riverside, CA, the most frequently searched job titles are:

What job categories do people searching Gpu Performance Engineer jobs in Riverside, CA look for?

The top searched job categories for Gpu Performance Engineer jobs in Riverside, CA are:

What cities near Riverside, CA are hiring for Gpu Performance Engineer jobs?

Cities near Riverside, CA with the most Gpu Performance Engineer job openings:

Gpu Performance Engineer jobs near you

Senior Perception Engineer

FieldAI

Irvine, CA

$160K - $1M/yr

Full-time

Posted 5 days ago

Job description

FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.


What You'll Get To Do
  • Design, build, and deploy perception systems for autonomous robots operating in complex real-world environments, taking ownership from initial design through on-robot deployment and long-term maintenance.
  • Develop new perception capabilities by leveraging existing model outputs where possible and designing new algorithms or perception tasks where needed.
  • Work extensively with LiDAR and vision data, with a strong emphasis on 3D perception and geometric reasoning as core components of the perception stack.
  • Develop and integrate multi-sensor perception algorithms, combining information across sensors to provide robust and reliable outputs in both simulation and real-world deployments.
  • Partner closely with planning and autonomy teams to define perception outputs that directly support downstream decision-making, navigation, and safety.
  • Debug perception and system-level issues in the field, including sensor timestamps, synchronization, calibration, data quality, coordinate frames, and hardware/software integration. Determine whether issues should be solved within perception or addressed upstream with the core platform team.
  • Bring algorithms all the way to physical robots, profiling, debugging, and optimizing them under real compute, latency, sensor, and environmental constraints.
  • Continuously evaluate and improve perception performance through offline evaluation, simulation, on-robot testing, and field validation.
  • Solve long-tail and safety-critical perception challenges by developing scalable data mining, training, and evaluation pipelines for rare real-world scenarios.
  • Ensure model quality across releases by developing evaluation methodologies, regression detection systems, and practical performance metrics-including ground-truth-free metrics where appropriate.
  • Improve the robustness, scalability, and maintainability of the perception stack, balancing rapid product development with long-term system quality.
What You Have
  • Bachelor's degree in Computer Science, Robotics, Machine Learning, or a related technical field; graduate degree preferred.
  • 4+ years of professional experience in machine learning, computer vision, robotics, or related areas, with substantial hands-on perception engineering experience.
  • Hands-on experience deploying perception systems on real-world robotic platforms; experience limited to simulation or offline datasets is not sufficient.
  • Strong experience working with LiDAR and vision sensors, particularly for 3D perception and real-world robotics applications.
  • Strong systems-level understanding of perception and its interaction with the broader autonomy stack, with the ability to reason about interfaces, latency, failure modes, and downstream behavior.
  • Experience with planning, navigation, or controls is a strong plus, especially where perception outputs directly influence robot behavior.
  • Experience debugging systems, including sensor data quality, synchronization, calibration, coordinate transforms, and failures observed only during real-world operation.
  • Ability to own complex perception subsystems end-to-end-from technical design and implementation through deployment, validation, debugging, and long-term maintenance.
  • Strong software engineering fundamentals and experience writing robust, production-quality C++.
  • Experience with CUDA and GPU optimization is highly desirable.
  • Background in autonomous vehicles, field robotics, mobile robotics, or similarly complex real-world autonomous systems.
  • Ability to operate effectively across algorithm, systems, and product boundaries and collaborate closely with perception, platform, planning, and field engineering teams.
What Sets You Apart
  • Experience integrating and calibrating custom sensor rigs (e.g., stereo or multi-LiDAR setups)
  • Prior experience contributing to a planning stack
  • Familiarity with CI/CD pipelines, performance regression testing, and benchmarking for perception systems
  • Demonstrated leadership in research, field operations, or mentoring junior engineers and researchers
$160,000 - $1,850,000 a year



Our salary range is generous and we consider each individual's background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.
 
Why Join FieldAI in Irvine?
In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics' hardest challenges: reliable deployment outside the lab. Our Field Foundational Models raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use.
You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.
 
Be Part of the Next Robotics Revolution
We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world.
 
Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like.
 
We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected status.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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