Research Scientist, RL for Dexterous Manipulation, Atlas

Are you passionate about using reinforcement learning to solve dexterous manipulation tasks? As an RL Research Scientist , you'll lead research projects on visual sim-to-real transfer and post-training of Vision-Language-Action (VLA) models. Your job is to turn unlabeled data from simulation or the real-world into robust real-world manipulation skills. You should push the frontier of what bimanual and multi-fingered systems can do in unstructured environments.

In this role, you will

• Develop novel algorithms for visual sim-to-real transfer with photorealistic rendering

• Design post-training recipes that improve pretrained VLA models on manipulation tasks

• Research reward modeling, and offline-to-online RL for large multimodal policies

• Close the sim-2-real gap through tactile sensing, vision, and system identification

• Train policies that generalize across objects, scenes, and embodiments

• Required Qualifications: PhD, in ML, Robotics, or a related field or a MS with 3+ years of experience

• Track record of first-author publications at top venues (CoRL, RSS, ICLR, NeuRIPS)

• Demonstrated experience training policies for dexterous or contact-rich manipulation

• Hands-on experience with VLA models, diffusion policies, or large behavior models

• Proficient in PyTorch and/or JAX, with experience training models at scale

• Strong software fundamentals and the ability to ship research code that runs reliably

• The ideal candidate has: Deployed vision-based manipulation policies on physical robots

• Deep knowledge of sim-to-real transfer techniques and photorealistic rendering

• Built training pipelines that combine RL, imitation learning, and large-scale pretraining

• Experience fine-tuning foundation models with RLHF, DPO, GRPO, or related methods

• Familiarity with tactile sensing, multi-fingered hands, or bimanual coordination

Why join us?

Direct impact on the policies powering our humanoid robots in the real world

Access to a world-class fleet of robots, simulation infrastructure, and compute

The chance to define what's possible for dexterous manipulation at scale

The pay range for this position is between $175,000 to $220,000 annually. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and a annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment. #LI-JM1