Robotics Software Researcher - Reinforcement Learning & Embodied AI

Acceler8; San Francisco (CA); Sur place; USD 180 000 - 240 000; Plein temps

Résumé du poste

Acceler8 Talent seeks a Robotics Software Researcher to advance learned control policies for embodied AI in real-time human collaboration. You will bridge interactive gaming environments with physical robotics, focusing on RL, imitation learning, and visuomotor control.

Responsibilities include building low-latency models, researching world models, planning, and sim-to-real transfer, while developing robust RL training pipelines in simulated and real contexts.

Qualifications

• PhD in Robotics, ML, or equivalent research experience.
• Publications at NeurIPS, ICLR, ICML, CoRL, RSS or similar conferences.
• Strong experience developing and training RL/IL policies.
• Proficiency in Python and deep learning frameworks (e.g., PyTorch).

Responsabilités

• Develop reinforcement learning, imitation learning and visuomotor policies.
• Build low-latency models translating perception into actions.
• Research world models, planning and hierarchical policies.
• Develop simulation environments and RL training pipelines.
• Explore sim-to-real transfer and human-AI collaboration.

Connaissances

RL policy training

Imitation learning

Visuomotor control

Python programming

PyTorch

Formation

PhD in Robotics or ML

Outils

PyTorch

Description du poste

Robotics Software Researcher | Reinforcement Learning & Embodied AI | San Francisco, CA

I'm partnering with a well-funded frontier AI research startup developing low-latency intelligent agents capable of collaborating with humans in real time.

They're looking for a Robotics Software Researcher to develop learned control policies, bridging interactive gaming environments and real world robotics.

The role:

• Develop reinforcement learning, imitation learning and visuomotor policies


• Build low-latency models that translate perception into actions


• Research world models, planning and hierarchical policies


• Develop simulation environments and RL training pipelines


• Explore sim-to-real transfer and human-AI cooperation

What they're looking for:

• PhD in Robotics, ML or equivalent research experience


• Publications at NeurIPS, ICLR, ICML, CoRL, RSS or similar conferences


• Strong experience developing and training RL/IL policies


• Python/PyTorch expertise


• Experience with embodied AI, VLAs or learned robotic control

Why consider it?

• Join a well-backed AI research lab working at the intersection of reinforcement learning, robotics and intelligent agents, with the opportunity to shape an emerging research direction.

Location:San Francisco, CA (City)