Proception.AI

www.proception.ai

1 Job

13 Employees

About the Company

Our mission is to advance humanoid robotics through cutting-edge innovations, driving the evolution and capabilities of humanoid robots worldwide

Listed Jobs

Company Name: Proception.AI
Job Title: AI & Robotics Research Engineer - Learned Dexterous Manipulation
Job Description: Job title: AI & Robotics Research Engineer – Learned Dexterous Manipulation Role Summary: Lead the design and deployment of scalable reinforcement learning (RL) pipelines for high‑degree‑of‑freedom humanoid and dexterous robotic hands. Build foundation models for manipulation tasks such as grasping, in‑hand reorientation, and tool use, and drive policy robustness to real‑world uncertainty across simulation and physical robot deployment. Expactations: • Self‑driven problem solver with curiosity for advanced RL and control methods. • Strong communication skills to collaborate with hardware, perception, and systems teams. • Ability to manage large‑scale experiments and iterate quickly on training pipelines. • Commitment to pushing beyond simulation limits in real‑world robotic control. Key Responsibilities: • Design and implement scalable RL systems for high‑DOF robots. • Develop foundation models and robust policies for grasping, in‑hand manipulation, and tool use. • Build and maintain physics‑accurate simulation environments in MuJoCo or Isaac Lab. • Apply advanced RL, imitation learning, and hybrid approaches to model complex object–hand dynamics. • Integrate multimodal feedback (vision, proprioception, tactile) for adaptive manipulation. • Design learning‑driven optimization of robot morphology and actuation strategies. • Collaborate with cross‑functional teams to deploy and validate policies on real robots. Required Skills: • Deep expertise in continuous‑control RL and policy optimization. • Strong background in probability, optimization, and linear algebra. • Proficiency in Python and C++ on Linux/Unix. • Hands‑on experience with robotics simulators (MuJoCo, Isaac Sim). • Knowledge of imitation learning, inverse RL, or hybrid learning techniques. • Experience training and deploying RL on real robotic hardware. • Familiarity with tactile sensing and contact‑rich manipulation (plus). Required Education & Certifications: • MS or PhD in Robotics, Computer Science, Machine Learning, or equivalent industry experience.

Palo alto, United states

On site

13-01-2026