Senior Research Engineer – Humanoid Manipulation

Field Ai; Boston (MA); On-site; USD 90,000 - 120,000; Full time

Job summary

Field Ai is seeking a Research Engineer in Boston, MA to enhance humanoid manipulation capabilities. This role emphasizes advancing robotics while translating breakthroughs into practical, scalable solutions. You will collaborate with diverse teams, driving projects from concept to deployment.

The ideal candidate has at least 4 years of experience in robotic manipulation, a relevant degree, and a strong knowledge of kinematics and control systems. Join a team committed to innovation and diversity in robotics.

Qualifications

• 4+ years of hands-on experience in robotic manipulation.
• Strong foundation in robot kinematics, dynamics, and control.
• Ability to work effectively in fast-paced, highly collaborative environments.

Responsibilities

• Design and evaluate manipulation strategies for humanoid robots.
• Translate research ideas into reliable robotic systems.
• Prototype quickly and validate results in the field.

Skills

Robotic manipulation

Robot kinematics

Machine learning

Teleoperation systems

Education

Bachelor's, Master's, or PhD in Robotics, Computer Science, Mechanical Engineering

Job description

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.

Location: Boston, MA.

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.

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.

Qualifications

• 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.
• 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 with field‑ready robotic systems.

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.