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

FieldAI

Robotics Autonomy Engineer: Simulation

Irvine, CA · On-site +1

$70K - $300K/yr

Experience with GPU programming (CUDA, PyTorch) or machine learning for robotics . * Background in ... Candidates and employees are always evaluated based on merit, qualifications, and performance. We ...

FieldAI

Robotics Autonomy Engineer: Simulation

Irvine, CA · On-site

$70K - $300K/yr

Experience with GPU programming (CUDA, PyTorch) or machine learning for robotics . * Background in ... Candidates and employees are always evaluated based on merit, qualifications, and performance. We ...

FieldAI

Robotics Autonomy Engineer: Simulation

Irvine, CA · On-site +1

$70K - $300K/yr

Experience with GPU programming (CUDA, PyTorch) or machine learning for robotics . * Background in ... Candidates and employees are always evaluated based on merit, qualifications, and performance. We ...

Hornet Acquisition Co LLC

Helpdesk Technician

Anaheim, CA · On-site

$70.30K - $80K/yr

Signia Aerospace is a global, integrated provider of high-performance systems and specialized ... Experience in manufacturing or engineering environments, including applications such as CAD, CAM ...

Hornet Acquisition Co LLC

Program Manager

Anaheim, CA · On-site

$150K - $170K/yr

Signia Aerospace is a global, integrated provider of high-performance systems and specialized ... Translate customer requirements into executable plans across engineering, manufacturing, supply ...

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How much do gpu performance engineer jobs pay per hour?

As of May 31, 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 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 Riverside, CA? For Gpu Performance Engineer jobs in Riverside, CA, the most frequently searched job titles 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

Embedded Systems Engineer, Robotics Hardware

FieldAI

Irvine, CA

Full-time

Posted 17 days ago

Job description

Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.

Hardware Team:
The Hardware Team at Field AI develops perception and compute payloads that power autonomous robotics systems in complex real-world environments. Our work spans the full hardware stack designing and integrating sensing systems (LiDAR, camera, TOF, IMU, GPS), embedded compute (CPUs, GPUs, microcontrollers, Linux, ROS), electrical systems (power distribution, communication), and mechanical components (structures, thermal regulation, ingress protection). The team focuses on both development (research, design, prototyping, testing) and operations (production, testing, QA, debugging). We’re a small, fast-moving team, and we care deeply about improving: 1) core capabilities, 2) system reliability, 3) system scalability. As a growing team we are also building operational systems and procedures from the ground up.
 
Embedded Compute Role:
As an Embedded Compute Engineer on the Hardware Team at Field AI, you will contribute to the architecture, configuration, and validation of the compute systems that serve as the backbone for our robotic platforms. Your work will span low-level firmware, Linux-based configuration, and system performance analysis across ARM and x86 SBC platforms. From firmware on microcontrollers to ROS data streams on SBCs, you’ll ensure the entire compute stack is optimized, reliable, and robust under field conditions. You will collaborate closely with the sensor, electrical, and autonomy teams to build tightly integrated solutions ready for deployment in challenging field environments. Additionally, while your focus will be on computing systems you will likely contribute across all hardware domains.
 
What You Will Get To Do
 
1. Compute System Design
  • Compute Architecture: Architect and configure embedded compute platforms (ARM/x86, SBCs) for robotic applications including evaluation, testing and selection.
  • Firmware & Software: Set up and customize Linux environments (Ubuntu, Yocto, JetPack), middleware (ROS), and I/O interfaces.
  • Systems Integration: Integrate compute with sensing and robotic systems. Analyze thermal, power, and bandwidth constraints to meet deployment and runtime requirements.
 
2. Compute System Implementation
  • Communications: Bring up sensors and peripherals using a range of protocols (USB, Ethernet, GMSL, I²C, SPI, CAN).
  • Data Pipelines: Build and maintain drivers, ROS nodes, and data acquisition pipelines for new hardware components.
  • Systems Configuration: Create configuration files, launch scripts, and firmware update workflows.
  • Testing: Conduct system-level tests such as thermal profiling, latency measurement, and power draw analysis.
  • Documentation & Budgets: Maintain flashing procedures, I/O maps, and debug kits. Manage compute and I/O budgets.
 
3. Compute System Production & Servicing
  • Build: Work with vendors to procure compute hardware. Develop QA checks for incoming units. Support payload integration and scaling.
  • Debug: Support root-cause analysis for boot, connectivity, and throughput issues.
  • Diagnostics Monitoring: Implement watchdogs, health checks, and other evaluation tools.  Monitor compute system performance across CPU, GPU, memory, I/O, and networking.
 
What You Have
 
  • Education: B.S., M.S., or Ph.D. in Computer Engineering, Robotics, Electrical Engineering, or a related field.
  • Experience Level: We are recruiting across a wide range of experience levels from entry level engineers to senior and staff engineers.
  • Embedded Systems: Experience with embedded platforms (Jetson, Raspberry Pi, x86 NUCs, custom SBCs).
  • Linux: Proficiency with Linux system configuration, scripting, and headless deployment tools.
  • Firmware: Strong skills in firmware development for microcontrollers, including bare-metal and RTOS environments.
  • Programming: Proficient in C++ and Python for embedded and application-level development.
  • Communication Protocols: Experience with USB, Ethernet, I²C, SPI, CAN, GMSL, and similar interfaces.
  • ROS Ecosystem: Familiarity with ROS, device drivers, TF, and data streaming/publishing.
  • Debugging: Comfort with hardware/software debugging tools (oscilloscopes, logs, power monitors, analyzers).
  • Systems Thinking: Ability to diagnose and optimize across compute, thermal, timing, and I/O layers.
 
What Will Set You Apart
 
  • Scaling: Experience taking systems from prototype to large scale production.
  • Field Environments: Experience developing systems for harsh field environments.
  • Deployed Robotics: Experience working on robotics deployed in real world settings such as autonomous vehicles, drones, or ruggedized robots.
  • Systems Level Robotics: Fluency across software, electrical, and mechanical systems.
  • Autonomy Software: Knowledge of autonomy stacks used in robotics. As well as how compute performance impacts autonomy algorithms.
Compensation and Benefits
Our salary range is between ($70,000 - $300,000 annual), but we take into consideration an individual's background and experience in determining final salary; base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience.  Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.

Why Join Field AI?
We are solving one of the world’s most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment.

You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.

Be Part of the Next Robotics Revolution
To tackle such ambitious challenges, we need a team as unique as our vision — innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We’re seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators.

We are headquartered in always-sunny Irvine, Southern California and have US based and global teammates. 

Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!



We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, 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. 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.