Research Scientist, RL for Dexterous Manipulation, Atlas

Boston Dynamics; Boston (MA); On-site; USD 175,000 - 220,000; Full time

Benefits offered by this job

Medical benefits

401(k)

Paid time off

Annual bonus

Job summary

Boston Dynamics is seeking an RL Research Scientist to lead projects on visual sim-to-real transfer and post-training of Vision-Language-Action models. You will turn unlabeled data from simulation or real world into robust dexterous manipulation skills for bimanual and multi-fingered systems in unstructured environments.

You will publish in top venues and push the frontier of manipulation with tactile sensing, world models, and large-scale RL.

Qualifications

• PhD in ML, Robotics or related field or MS with 3+ years experience.
• Track record of first-author publications at top venues (CoRL, RSS, ICLR, NeuRIPS).
• Hands-on experience training policies for dexterous or contact-rich manipulation.
• Experience with VLA models, diffusion policies, or large behavior models.
• Proficient in PyTorch and/or JAX with scalable model training.
• Strong software fundamentals and ability to ship research code.

Responsibilities

• Develop novel algorithms for visual sim-to-real transfer with photorealistic rendering.
• Design post-training recipes to improve pretrained VLA models on manipulation tasks.
• Research reward modeling and offline-to-online RL for large multimodal policies.
• Close the sim-to-real gap through tactile sensing, vision, and system identification.
• Train policies that generalize across objects, scenes and embodiments.

Education

PhD or MS with 3+ years experience

Tools

PyTorch

JAX

Job description

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.