Electrical Engineer, Robotics Hardware- Part-time Internship

Who are We?

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.

Learn more at

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.

At FieldAI, we build autonomous robotic systems that operate in demanding, real-world environments where tight integration between hardware and software is critical. We’re looking for an Electrical Engineer
- Part-time Intern to assist in the design and development of electrical systems and components. In this role, you will sit at the interface of mechanical, electrical, embedded software, and autonomy systems. Assist in the design and development of electrical systems and components. Conduct testing and analysis of electrical circuits and systems. Collaborate with senior engineers on project tasks and problem-solving.

$27 - $30 an hour

• Education: Current B.S., M.S., or Ph.D. student in Robotics, Electrical Engineering, Mechanical Engineering or a related field.
• Robotic Platforms: Familiarity with diverse robotic platforms, their capabilities, limitations, and trade-offs, and how to adapt payloads accordingly.
• Robotics Firmware & APIs
  :
  Hands‑on experience applying robot SDKs, APIs, and native libraries to implement and validate advanced maneuvers or joint-level control.
• ROS Ecosystem: Familiarity with ROS, device drivers, TF, and data streaming/publishing.
• Testing & Validation
  :
  Comfort designing and executing repeatable test protocols for mobility, stability, runtime, and terrain handling; experience verifying manufacturer specifications before and after payload integration.
• Field Systems
  :
  Experience designing or supporting complementary systems such as docking solutions, charging stations, or protective enclosures.

• Scaling: Experience taking systems from prototype through design iteration.
• 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 mechanical, electrical, and software systems.
• Reliability Engineering: Experience designing to meet IP ratings, MIL-STD, or equivalent ruggedness standards.

Our salary range is generous and 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.

At Field AI, we believe the most effective way to collaborate and solve complex challenges is by working together in person. This is a fully onsite role, and candidates will be expected to work from our Irvine, CA office. In-person engagement is essential to our success, and we offer flexible working hours to support focus and work-life balance.

We are solving one of the world’s most complex challenges: deploying robots in unstructured,…