Field AI

Robotics Research Internship, Humanoid Manipulation

Boston, MA
Python C++ ROS ROS 2 Machine Learning AI
Description

1.53 Robotics Research Internship, Humanoid Manipulation (Summer 2026) | PhD Internship

Team: Research

Location: Boston, MA

Commitment: Internship

Workplace Type: onsite

FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop 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.

We are offering a Summer 2026 internship focused on humanoid manipulation for PhD students interested in advancing embodied intelligence on real robotic systems. As a research intern, you will work at the intersection of robotics research and applied engineering, contributing to manipulation capabilities for humanoid robots that directly support FieldAI’s autonomy and robot learning efforts.
 
You will collaborate closely with Field AI research scientists and engineers to design experiments, develop manipulation systems, and test ideas on real hardware. This internship emphasizes translating research into practical, scalable systems, while also contributing to longer-term efforts around embodiment-agnostic robotics foundation models.

What You Will Get To Do

  • Advance Humanoid Manipulation Research
  • Design, implement, and evaluate manipulation strategies for humanoid robots across diverse tasks.
  • Explore loco-manipulation problems that integrate perception, planning, and control.
  • Contribute to research projects from early ideas through on-robot experimentation.
  • Build Systems That Bridge Research and Deployment
  • Translate research concepts into working robotic systems tested on real hardware.
  • Develop experimental setups and tooling to support data collection and evaluation.
  • Help ensure manipulation systems are robust, reproducible, and field-relevant.
  • Contribute to Robotics Foundation Model Development
  • Support data collection pipelines used to train robotics foundation models.
  • Work with embodiment-agnostic representations to enable transfer across robot platforms.
  • Collaborate with researchers to integrate manipulation data into scalable learning frameworks.
  • Collaborate Across Disciplines
  • Partner with mechanical and electrical engineers on hardware integration and system bring-up.
  • Work with teleoperators and field teams to refine interfaces and improve manipulation outcomes.
  • Engage closely with researchers and engineers to align experiments with broader autonomy goals.
  • Rapidly Iterate and Learn
  • Prototype quickly, run experiments on hardware, and analyze results rigorously.
  • Balance exploratory research with concrete deliverables over the course of the internship.
  • Debug system-level issues spanning software, hardware, and learning.

What You Have

  • Current PhD student in Robotics, Computer Science, Mechanical Engineering, AI/ML, or a closely related field.
  • Research experience in robotic manipulation, loco-manipulation, or related robotics domains.
  • Strong foundation in robot kinematics, dynamics, and control.
  • Proficiency in Python and/or C++, with experience using robotics or ML tooling.
  • Experience designing experiments and evaluating results on robotic systems (simulation or hardware).
  • Curiosity, initiative, and a strong interest in embodied intelligence and real-world robotics.

The Extras That Set You Apart

  • Prior experience working with humanoid robots or dexterous robotic hands.
  • Background in learning-based manipulation, including imitation learning or reinforcement learning.
  • Hands-on experience running experiments on real robot hardware.
  • Familiarity with ROS or ROS 2.
  • Publications, preprints, or open-source contributions in robotics or AI.
  • Interest in bridging cutting-edge research with practical, field-ready robotic systems.
Why Join Field AI?
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 R&D organization is growing and anchored in Boston, with close collaboration across our teams in Southern California and with colleagues around the US and globally.

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.
Field AI
Field AI

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