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Transforming industrial operations through physically embodied robotic AI and superhuman autonomy.
The Role
FieldAI is transforming how robots interact with the real world. We build risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use.
In Pittsburgh, we’re pushing the frontier of embodied intelligence by designing robot learning systems that scale across tasks, environments, and robot embodiments. We work on robotics foundation models, from vision and language to control, and we deploy what we build on real robots solving real problems in unstructured, real-world settings.
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’ll Get To Do
- Conduct Research in Robot Learning
- Investigate learning-based approaches for robotic autonomy, including reinforcement learning, imitation learning, and multimodal foundation models.
- Explore methods for learning transferable skills across tasks, environments, and robot embodiments.
- Contribute to research projects from early ideas through experimental validation.
- Advance Robotics Foundation Models
- Work on adapting large-scale vision, language, and multimodal models for robotics applications.
- Support research on grounding perception and reasoning models in real-world robot behavior.
- Collaborate on embodiment-agnostic representations that enable transfer across platforms.
- Large-Scale Training and Experimentation
- Design and run training pipelines using modern ML frameworks.
- Experiment with sim-to-real transfer, domain adaptation, and data scaling strategies.
- Analyze results rigorously and iterate quickly on research hypotheses.
- Deploy and Validate on Real Robots
- Test and validate research ideas on real robotic platforms, including manipulators and mobile robots.
- Help address real-world robotics challenges such as perception noise, partial observability, and system robustness.
- Participate in field testing and data collection efforts.
- Collaborate and Learn
- Partner closely with FieldAI research scientists and engineers across disciplines.
- Contribute to internal research discussions, reviews, and technical presentations.
- Where appropriate, contribute to publications, preprints, or open-source projects.
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.
- Proficiency in Python and experience with ML frameworks such as PyTorch.
- 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.
Why Join FieldAI?
FieldAI is tackling one of robotics’ hardest problems: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ advance perception, planning, localization, and manipulation with an emphasis on explainability and safety, so our systems can be trusted where it matters most.
You will work alongside a world-class team that values creativity, resilience, and bold thinking. We bring a decade-long track record of real-world deployments, strong performance in DARPA challenges, and experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX.
Our Pittsburgh team is growing and focused on robot learning and embodied intelligence, building and deploying learning systems that generalize across tasks and robot embodiments. You will work on research that connects foundation models, large-scale training, and real-world robotic performance, with a clear path from ideas to field capability.
Be Part of the Next Robotics Revolution
Solving problems at this scale takes a team as unique as the mission. We are looking for people who push beyond conventional approaches, enjoy tackling tough and ambiguous questions, and bring interdisciplinary perspective. Our success depends on exceptional AI researchers and engineers, as well as strong software developers, product designers, field deployment experts, and communicators who can turn breakthroughs into real capability.
We are headquartered in Mission Viejo (Irvine adjacent), Southern California, with teammates across the US and around the world. Join us to shape the future of embodied intelligence as part of a fun, close-knit team building systems that work in the real world.
Equal Opportunity
FieldAI celebrates diversity and is committed to creating an inclusive environment for all employees. Candidates and employees are evaluated based on merit, qualifications, and performance. We do not discriminate on the basis of race, color, religion, sex, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected status.
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The Company
What We Do
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.
