Backed by 500 Global.
About the role
We are looking for a Reinforcement Learning Engineer to join our Manipulation team, focused on dexterous grasping. Our goal is to ship capable, reliable grasping policies on real hardware with high-DOF robotic hands. We are looking for someone who can follow recent advances in reinforcement learning and related learning-based methods, judge what is practically useful, and adapt those ideas on our platform.
What they're looking for
- BS, MS, or PhD in Robotics, Computer Science, Machine Learning, or a related field
- 2+ years of hands-on experience in reinforcement learning for robotic manipulation, exceptional recent graduates from relevant research labs will be considered
- Demonstrated ability to read, understand, and implement ideas from recent robotics and machine learning research
- Hands-on experience training RL agents for robotic manipulation tasks, including reward shaping and policy evaluation
- Experience with sim-to-real transfer: domain randomization, physics tuning, or real-world policy validation on hardware
- Proficiency in Python and deep learning frameworks (PyTorch, JAX), along with RL libraries such as rsl_rl or skrl
More about this role
Persona AI is developing and commercializing rugged, multi-purpose humanoid robots that perform real work. Persona's founding team has a decades-long history in humanoid robotics, bionics, and product development delivering robust hardware that has touched the stars, worked miles below the surface of the ocean, roamed Disney Parks, and has even been featured on a US postage stamp. Our mission is focused squarely on shipping beautiful, reliable products at massive scale, while building a customer-focused team to achieve these aims.
We are looking for a Reinforcement Learning Engineer to join our Manipulation team, focused on dexterous grasping. Our goal is to ship capable, reliable grasping policies on real hardware with high-DOF robotic hands. We are looking for someone who can follow recent advances in reinforcement learning and related learning-based methods, judge what is practically useful, and adapt those ideas on our platform. If you are earlier in your career but exceptional, we want to hear from you; equally, a more experienced candidate who brings deep RL expertise will thrive here.
Train and iterate on reinforcement learning policies for complex grasping tasks including...
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