Robot Control Systems Intern

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Summary

Location

Irvine, United States

Salary

$47 - $53/hour

Work

Internship

Key Benefits
Equity

About this Job

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 athttps://fieldai.com.

About the Job

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 a Robotics Controls Intern to join our autonomy team and work directly alongside our senior engineers to tackle complex control challenges for large-scale, off-road vehicles. In this highly impactful internship, you will help bridge the gap between advanced control theory and field-deployable products. You will dive into system dynamics modeling, optimize GPU-accelerated control libraries, and develop computationally constrained control schemes for heterogeneous platforms, ranging from massive off-road vehicles to smaller, resource-limited robotic systems. Furthermore, you will play a critical role in designing and implementing low-latency safety layers that protect our robots in both tele-operated and fully autonomous modes. This is a hands-on role for a driven researcher or engineer who wants to see their code running on real vehicles in extreme, unstructured environments.

What You Have

  • Currently pursuing a Ph.D. or Master’s degree in Robotics, Computer Science, Mechanical Engineering, Electrical Engineering, or a highly related field with a focus on control systems.

  • Deep theoretical understanding and practical experience with advanced control methodologies, particularly predictive and sampling-based control (e.g., MPPI, MPC).

  • Strong proficiency in GPU programming (specifically CUDA) with a track record of accelerating and optimizing complex algorithms for real-time execution.

  • Hands-on experience taking control algorithms out of simulation and deploying them onto physical robots in real-world environments.

  • Experience with system dynamics modeling, system identification, and training learning models for robotic platforms.

  • Strong software engineering skills in C++ and Python, with the ability to write clean, deployable code for robotics applications.

  • Hands-on experience with Linux, ROS1/2 and Docker


The Extras That Set You Apart

  • Experience working with large-scale, off-road, or high-speed autonomous wheeled vehicles in unstructured environments.

  • Experience designing and implementing low-latency safety layers or safety controllers for autonomous or tele-operated systems.

  • Demonstrated ability to reduce compute costs and adapt computationally heavy control schemes for hardware-constrained systems.

  • Experience maintaining or significantly contributing to open-source robotics control libraries.

  • Familiarity working within established, fast-paced autonomy engineering teams and seamlessly integrating with existing software stacks.

  • Knowledge of containerization (Kubernetes) and modern DevOps practices.

$47 - $53 an hour

Compensation

The salary range for this role is $47.00-$53.00/hr. The actual offer for this position will be based on factors such as relevant experience, competencies, certifications, and how well the candidate meets the qualifications outlined above. Part of our compensation package also includes full benefits, equity, and generous time.

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. Witha 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.

About the Company

Field AI logo

Field AI

Privately Held
Robotics Software & AIEnergy & MiningConstruction & Agriculture

FieldAI is pioneering the development of a field-proven, hardware agnostic brain technology that enables many different types of robots to operate autonomously in hazardous, offroad, and potentially harsh industrial settings – all without GPS, maps, or any pre-programmed routes.

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