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Proception.AI · 6 hours ago

AI & Robotics Research Engineer - Learned Dexterous Manipulation

Palo Alto, CA

Full-time

Onsite

Senior Level

$150K/yr - $250K/yr

Proception.AI is seeking an expert in reinforcement learning to help build foundation models for dexterous humanoid manipulation. The role involves leading the design of scalable RL pipelines, training robust policies on high-DOF robotic hands, and deploying intelligent behaviors to enhance real-world robotic control.

Artificial Intelligence (AI)RoboticsSoftware Engineering

Responsibilities

Design and deploy scalable RL systems for high-DOF humanoid and dexterous robotic hands

Develop foundation models for manipulation tasks such as grasping, in-hand reorientation, and tool use

Train policies that are robust to real-world uncertainty, including contact variation, sensor noise, and hardware drift

Build and maintain physics-accurate simulation environments using MuJoCo or Isaac Lab

Apply advanced RL and control techniques to model complex object–hand interactions

Develop imitation and hybrid learning pipelines from human demonstrations

Leverage multimodal feedback (vision, proprioception, tactile sensing) for adaptive manipulation

Explore learning-driven optimization of robot hardware, morphology, and actuation strategies

Work closely with hardware, perception, and systems teams to deploy policies on real robots

Qualification

Reinforcement LearningPolicy OptimizationContinuous-Control SystemsPythonC++Robotics SimulatorsImitation LearningProbabilityOptimizationLinear AlgebraCuriousExcited to Build SystemsSelf-driven