Hiring: Reinforcement Learning Engineer, Grasping Company: Persona AI Location: Houston, TX Job Posted Time: 2026-09-12 17:57:42 Employment Type: Full-time Target Skills & Keywords: Reinforcement Learning, Robotic Manipulation, Sim-to-Real Transfer, Python, PyTorch, MuJoCo, Isaac Sim, Tactile Sensing Experience: 2+ years of hands-on experience in reinforcement learning for robotic manipulation. Exceptional recent graduates from relevant research labs will also be considered. Required Skills: - Train and iterate on reinforcement learning policies for complex grasping tasks. - Implement and refine sim-to-real transfer pipelines. - Develop reward functions, curriculum strategies, and training environments. - Run experiments on real robots and evaluate policy behavior. - Monitor and adapt state-of-the-art research in learning-based grasping. - Collaborate with software teams to deploy end-to-end grasping systems. - Integrate tactile sensing and feedback into grasp policies. Qualifications: - BS, MS, or PhD in Robotics, Computer Science, Machine Learning, or a related field. - Proficiency in Python and deep learning frameworks (PyTorch, JAX). - Experience with RL libraries such as rsl_rl or skrl. - Hands-on experience training RL agents for robotic manipulation tasks. - Experience preparing meshes and collision geometries for RL environments. Compensation: Competitive compensation, performance-based bonus, 99% employer-covered medical benefits, early-stage equity, competitive PTO, and a company-wide paid winter break. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don’t miss this opportunity to join a forward-thinking team!