Robotics Research Internship (Humanoid Manipulation)

Location: Boston, MA; on-site

Salary: $40–$60 per hour

Company

hirify.global develops risk-aware, reliable, field-ready AI and robotics systems for unstructured real-world environments, including foundational models for perception, planning, localization, and manipulation.

What you will do

• Design, implement, and evaluate manipulation strategies for humanoid robots across diverse tasks.
• Explore loco-manipulation problems combining perception, planning, and control.
• Develop systems aimed at improving dexterity beyond human teleoperation.
• Support data-collection pipelines and scalable learning frameworks for robotics foundation models.
• Collaborate with researchers, engineers, teleoperators, and field teams on experiments, interfaces, and autonomy goals.
• Integrate manipulation systems with mechanical and electrical hardware and support system bring-up.

Requirements

• Current PhD student in robotics, computer science, mechanical engineering, electrical engineering, AI/ML, or a 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 machine-learning tools.
• Experience designing experiments and evaluating results in simulation or on robotic hardware.
• Publications in leading robotics journals or conferences are expected.

Nice to have

• Experience with humanoid robots or dexterous robotic hands.
• Background in imitation learning or reinforcement learning for manipulation.
• Hands-on experience with real robot hardware.
• Familiarity with ROS or ROS 2.
• Robotics or AI publications, preprints, or open-source contributions.

Culture & Benefits

• Research is connected to real-world deployment and field use.
• Opportunity to collaborate with internal and external researchers.
• Support for publishing research in leading robotics conferences or journals.
• Interdisciplinary collaboration across AI, software, mechanical, electrical, and field engineering.
• Work with a team focused on explainable, safe, and reliable embodied intelligence.