Humanoid Manipulation Engineer — Field-Ready Robotics

FieldAI; Boston (MA); On-site; USD 180,000 - 300,000; Full time

Job summary

FieldAI is seeking a Research Engineer in Boston to advance humanoid manipulation, building and testing control strategies that enable autonomous loco-manipulation on humanoid robots. You will collaborate with researchers and engineers to design novel manipulation approaches and feed into FieldAI’s robot learning pipelines.

You will also help advance robotics foundation models that are embodiment-agnostic, focusing on translating breakthroughs into practical, scalable autonomy for real-world

Qualifications

• Bachelor’s, Master’s, or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field.
• 4+ years 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.

Responsibilities

• Advance Humanoid Manipulation Research and Development by designing, implementing, and evaluating manipulation strategies.
• Drive projects from 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 in real-world conditions.
• Collaborate across disciplines with mechanical/electrical engineers and field teams.

Skills

Robotics manipulation

Kinematics

Team collaboration

Problem solving

Education

Robotics/CS/ME degree

Job description

FieldAI is seeking a Research Engineer in Boston to advance humanoid manipulation, building and testing control strategies that enable autonomous loco-manipulation on humanoid robots. You will collaborate with researchers and engineers to design novel manipulation approaches and feed into FieldAI’s robot learning pipelines.

You will also help advance robotics foundation models that are embodiment-agnostic, focusing on translating breakthroughs into practical, scalable autonomy for real-world