Agents and embodied systems

Robot learning and manipulation

Robot learning and manipulation is the work of teaching machines physical skills, using simulation to train and real-world testing to check the result. AI companies need it to turn capable models into systems that can act reliably on objects.

Models that understand language and images are now being asked to move things in the real world. That pulls robotics, control and ML into the same team. The hires are tricky because the skills rarely sit in one person. A strong ML researcher may never have faced sensor noise or a worn gripper. A strong roboticist may not have trained policies at scale. Safety and hardware integration stay separate constraints, so the best candidates respect them.

Hiring now 2Emerging 1

Roles in this family

3 roles

Hiring nowRobot Learning EngineerA Robot Learning Engineer trains policies that let robots complete defined physical tasks reliably. The work turns a promising demo into behaviour a…Hiring nowRobot Manipulation ResearcherA Robot Manipulation Researcher builds the grasping and object-interaction methods that let robots handle real things reliably. They turn lab demos…EmergingVision-Language-Action ResearcherA Vision-Language-Action Researcher builds models that turn instructions and camera input into safe, bounded robot actions. They matter because they…

Where the people come from

Robotics, control, mechanical/electrical engineering or ML

Not to be confused with. Physical safety and hardware integration remain independent constraints.

Core skills

  • Reinforcement learning
  • Computer vision
  • Robotics and control
  • Simulation and digital twins

Where it is used

  • Robotics and industrial automation
  • Manufacturing
  • Supply chain and logistics

More in Agents and embodied systems

Tool-using agents and workflow orchestration0 rolesMulti-agent coordination and economics0 rolesAutonomous navigation and field robotics0 rolesSimulation, digital twins and physical AI assurance0 roles

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