Senior Research Engineer – Humanoid Manipulation

Overview

Field

AI 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 looking for a Research Engineer to join our growing humanoid manipulation efforts. In this role, you will work at the intersection of robotics research and applied engineering, building, testing, and refining manipulation capabilities that accelerate autonomous control and loco-manipulation on humanoid robots. You will collaborate closely with research scientists, engineers, and product partners to design novel manipulation strategies and deliver systems that directly feed into Field AI’s robot learning pipelines.

You will also play a key role in advancing robotics foundation models designed to be embodiment agnostic, with an initial focus on humanoid platforms. This role is about pushing the frontier of manipulation research while ensuring that breakthroughs translate into practical, scalable autonomy in real-world environments.

• Advance Humanoid Manipulation Research and Development
• Design, implement, and evaluate manipulation strategies for humanoid robots across a wide range of tasks
• Drive projects from early concepts through on-robot testing and deployment
• Contribute to loco-manipulation capabilities that integrate perception, control, and planning
• Build Systems That Bridge Research and Deployment
• Translate research ideas into reliable robotic systems that operate in real-world conditions
• Ensure systems are robust, reproducible, and aligned with data collection and learning objectives
• Develop experimental infrastructure to support rapid iteration and evaluation
• Contribute to Robotics Foundation Model Development
• Support large-scale data collection and learning pipelines powering robotics foundation models
• Ensure manipulation systems and datasets remain embodiment agnostic, enabling transfer across robot platforms
• Collaborate with research scientists to integrate manipulation data into scalable robot learning frameworks
• Collaborate Across Disciplines
• Partner with mechanical and electrical engineers on hardware integration and system bring-up
• Work closely with teleoperators and field teams to refine interfaces and improve manipulation performance
• Act as a connective layer between autonomy research and applied robotics engineering
• Rapidly Iterate and Deliver
• Prototype quickly, run experiments on hardware, and validate results in the field
• Balance exploratory research with concrete deliverables that support near-term goals
• Debug complex system-level issues spanning software, hardware, and learning

• Bachelor’s, Master’s, or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field
• 4+ years of hands-on experience in robotic manipulation in academic or industry settings.
• Strong foundation in robot kinematics, dynamics, and control, with a focus on manipulation
• Proven experience implementing and evaluating robotic systems on real hardware
• Strong software development skills in Python and/or C++, with experience using robotics middleware such as ROS or ROS 2
• Ability to work effectively in fast-paced, highly collaborative environments
• Curiosity, ownership, and the confidence to challenge assumptions and propose new approaches

• Experience working with humanoid robots or multi-fingered robotic hands
• Background in learning-based manipulation, including imitation learning or reinforcement learning
• Familiarity with teleoperation systems and human-in-the-loop data collection
• Publications or open-source contributions in top robotics venues
• Experience with large-scale robotics data collection and dataset management
• Strong interest in bridging cutting-edge research…