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Entry Level Gpu Engineer Jobs (NOW HIRING)

Aurora Innovation

Software Engineer I

Mountain View, CA · On-site

$116K - $174K/yr

Profile and optimize code to ensure efficient use of limited CPU, GPU, and memory resources on the ... LI-Entry-Level Working at Aurora At Aurora, we bring together extraordinarily talented and ...

Viridien

Research Geophysicist

Houston, TX · Hybrid

You will also work closely with Software Engineers on the development, deployment, and improvement ... Performance based monthly bonus averaging at 10-15% at entry level ( contingent on financial ...

Viridien

Research Geophysicist

Houston, TX · Hybrid

You will also work closely with Software Engineers on the development, deployment, and improvement ... Performance based monthly bonus averaging at 10-15% at entry level ( contingent on financial ...

Cgg

Research Geophysicist

Houston, TX · Hybrid

You will also work closely with Software Engineers on the development, deployment, and improvement ... Performance based monthly bonus averaging at 10-15% at entry level ( contingent on financial ...

Supermicro

Content Designer

San Jose, CA

$33 - $45/hr

We are seeking a Content Designer and an entry-level industry writer to own the production of ... Understanding of CPU and GPU general technology Qualifications: * 2+ Years of high-intensity ...

Super Micro Computer

Content Designer

San Jose, CA · On-site

$33 - $45/hr

We are seeking a Content Designer and an entry-level industry writer to own the production of ... Understanding of CPU and GPU general technology Qualifications: * 2+ Years of high-intensity ...

Nebius

Sales Development Representative, Tavily

Austin, TX · On-site

$90K - $120K/yr

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we ... entry-level candidates). * You are in Austin and excited about an in-person office environment ...

Hut 8

Operations Coordinator - Highrise.ai

Miami, FL

This is an entry-level role designed for a young generalist who wants to enter a fast- moving AI ... Genuinely curious about AI, GPU infrastructure, and emerging technology * Comfortable in a fast ...

Hut 8

Operations Coordinator - Highrise.ai

Miami, FL · On-site

This is an entry-level role designed for a young generalist who wants to enter a fast- moving AI ... Genuinely curious about AI, GPU infrastructure, and emerging technology * Comfortable in a fast ...

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Entry Level Gpu Engineer information

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$40.5K

$86.4K

$142.5K

How much do entry level gpu engineer jobs pay per year?

As of Jun 10, 2026, the average yearly pay for entry level gpu engineer in the United States is $86,381.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $103,500.00 per year, depending on experience, location, and employer.

What is the difference between Entry Level Gpu Engineer vs Entry Level Hardware Engineer?

AspectEntry Level Gpu EngineerEntry Level Hardware Engineer
Required CredentialsBachelor's in Computer Engineering, Electrical Engineering, or related field; knowledge of GPU architectureBachelor's in Electrical Engineering, Computer Engineering, or related; understanding of hardware design
Work EnvironmentDesigning and optimizing GPU hardware and software; collaborating with software teamsDeveloping and testing various hardware components; working in labs or manufacturing settings
Industry UsagePrimarily in graphics, gaming, AI, and high-performance computing sectorsBroadly in electronics, consumer devices, and industrial equipment

While both roles require a background in electrical or computer engineering, Entry Level Gpu Engineers focus on GPU-specific hardware and software development, often within graphics and AI industries. Entry Level Hardware Engineers have a broader scope, working on various hardware components across multiple sectors. The roles differ mainly in specialization and application focus.

What are the key skills and qualifications needed to thrive as an Entry Level GPU Engineer, and why are they important?

To thrive as an Entry Level GPU Engineer, you need a solid background in computer engineering or computer science, with strong programming skills in C/C++ and an understanding of graphics algorithms or parallel computing. Familiarity with GPU programming frameworks like CUDA or OpenCL, and experience using development tools such as debuggers and profilers, are typically required. Analytical thinking, problem-solving abilities, and effective teamwork are important soft skills that help navigate complex technical challenges. These skills and qualities are essential for developing efficient GPU solutions and contributing to collaborative engineering projects.

What does an Entry Level GPU Engineer do?

An Entry Level GPU Engineer assists in designing, developing, and testing graphics processing units (GPUs) and related software. They typically work on low-level programming, debugging hardware issues, and optimizing performance under the guidance of more experienced engineers. Their role may also include writing drivers, collaborating with hardware and software teams, and learning industry-standard tools and processes. This position is a great starting point for those interested in computer graphics, parallel computing, or hardware engineering.

What are some typical projects an Entry Level GPU Engineer might work on during their first year?

As an Entry Level GPU Engineer, you might assist with optimizing graphics drivers, debugging performance issues, or supporting the development of new GPU features alongside senior engineers. You could also be involved in testing and validating hardware or software components, writing scripts for automation, and contributing to documentation. These projects provide valuable experience in GPU architecture and software-hardware interaction, while also fostering collaboration with cross-functional teams such as software developers, QA engineers, and hardware designers.
More about Entry Level Gpu Engineer jobs
What cities are hiring for Entry Level Gpu Engineer jobs? Cities with the most Entry Level Gpu Engineer job openings:
What are the most commonly searched types of Gpu Engineer jobs? The most popular types of Gpu Engineer jobs are:
What states have the most Entry Level Gpu Engineer jobs? States with the most job openings for Entry Level Gpu Engineer jobs include:
What job categories do people searching Entry Level Gpu Engineer jobs look for? The top searched job categories for Entry Level Gpu Engineer jobs are:
Entry Level Gpu Engineer jobs near you
Infographic showing various Entry Level Gpu Engineer job openings in the United States as of June 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 100% In-person job distribution, with an average salary of $86,381 per year, or $41.5 per hour.

Embedded Systems Engineer, Robotics Hardware

FieldAI

Irvine, CA

Full-time

Posted 3 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, IC, 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, IC, 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.
$70,000 - $300,000 a year
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.
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