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Robotics Research Intern, Robot Learning (Summer 2026) | PhD Internship

Field-ai
United States
Posted April 24, 2026
Internship 50 - 53 USD per-hour-wage

Job Overview

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.
 
We are offering a Summer 2026 internship in Robot Learning for students interested in advancing embodied intelligence through large-scale learning, foundation models, and real-world robotic deployment. As a research intern, you will work closely with FieldAI researchers and engineers to explore novel approaches to robot learning and autonomy, with a focus on scalable methods that generalize across tasks and embodiments.
 
This internship is designed for PhD students who want to connect cutting-edge AI research with practical robotics systems. You will have the opportunity to design experiments, develop learning pipelines, and validate ideas on real robotic platforms, contributing directly to FieldAI’s deployed autonomy stack.

What You Have:

  • Current PhD student in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.

  • Research experience in robot learning, reinforcement learning, imitation learning, or related areas.

  • Strong foundation in machine learning fundamentals and experimental methodology.

  • Develop multi-modal data collection platform for day/night robot navigation data collection

  • Collect high-quality datasets for reproducible and comparable research and evaluation

  • Summarize and publish learnings in high-quality robot research conference or journal

  • Ability to work independently while collaborating effectively in a research environment.

  • Strong interest in embodied intelligence and real-world robotics systems.

The Extras That Set You Apart

  • Prior experience working with real robot platforms.

  • Familiarity with ROS or ROS 2.

  • Experience with large-scale or distributed training systems.

  • Publications or open-source contributions in robotics or AI.

  • Background in perception, planning, or control for robotics.

  • Interest in bridging foundational research with deployed robotic systems.

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.
 
We are offering a Summer 2026 internship in Robot Learning for students interested in advancing embodied intelligence through large-scale learning, foundation models, and real-world robotic deployment. As a research intern, you will work closely with FieldAI researchers and engineers to explore novel approaches to robot learning and autonomy, with a focus on scalable methods that generalize across tasks and embodiments.
 
This internship is designed for PhD students who want to connect cutting-edge AI research with practical robotics systems. You will have the opportunity to design experiments, develop learning pipelines, and validate ideas on real robotic platforms, contributing directly to FieldAI’s deployed autonomy stack.

What You Have:

  • Current PhD student in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.

  • Research experience in robot learning, reinforcement learning, imitation learning, or related areas.

  • Strong foundation in machine learning fundamentals and experimental methodology.

  • Develop multi-modal data collection platform for day/night robot navigation data collection

  • Collect high-quality datasets for reproducible and comparable research and evaluation

  • Summarize and publish learnings in high-quality robot research conference or journal

  • Ability to work independently while collaborating effectively in a research environment.

  • Strong interest in embodied intelligence and real-world robotics systems.

The Extras That Set You Apart

  • Prior experience working with real robot platforms.

  • Familiarity with ROS or ROS 2.

  • Experience with large-scale or distributed training systems.

  • Publications or open-source contributions in robotics or AI.

  • Background in perception, planning, or control for robotics.

  • Interest in bridging foundational research with deployed robotic systems.

What You Have:

  • Current PhD student in Robotics, Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.

  • Research experience in robot learning, reinforcement learning, imitation learning, or related areas.

  • Strong foundation in machine learning fundamentals and experimental methodology.

  • Develop multi-modal data collection platform for day/night robot navigation data collection

  • Collect high-quality datasets for reproducible and comparable research and evaluation

  • Summarize and publish learnings in high-quality robot research conference or journal

  • Ability to work independently while collaborating effectively in a research environment.

  • Strong interest in embodied intelligence and real-world robotics systems.

The Extras That Set You Apart

  • Prior experience working with real robot platforms.

  • Familiarity with ROS or ROS 2.

  • Experience with large-scale or distributed training systems.

  • Publications or open-source contributions in robotics or AI.

  • Background in perception, planning, or control for robotics.

  • Interest in bridging foundational research with deployed robotic systems.

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. 
 
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.

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