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Irvine, California, United States
Onsite
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 https://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.
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
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.
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.