Boston Dynamics

Research Scientist, RL for Dexterous Manipulation, Atlas

Boston Dynamics$175K — $220K *
Consumer Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD in ML, Robotics, or related field, or MS with 3+ years experience
  • Proven first-author publications in top-tier conferences (CoRL, RSS, ICLR, NeuRIPS)
  • Hands-on experience with dexterous or contact-rich manipulation training
  • Experience with VLA models, diffusion policies, or large behavior models
  • Proficient in PyTorch and/or JAX for training models at scale
  • Strong software fundamentals with ability to deliver reliable research code

Responsibilities

  • Develop novel algorithms for visual sim-to-real transfer using photorealistic rendering
  • Design post-training strategies to enhance pretrained VLA models for manipulation
  • Research reward modeling and offline-to-online reinforcement learning for large multimodal policies
  • Bridge the sim-to-real gap utilizing tactile sensing, vision, and system identification
  • Train robust policies that generalize across varying objects, scenes, and robotic embodiments

Benefits

  • Direct impact on humanoid robot policies in the real world
  • Access to advanced robotic fleet, simulation infrastructure, and high-performance computing resources
  • Opportunity to redefine capabilities in dexterous manipulation on a large scale
Full 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.

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About Boston Dynamics

Boston Dynamics is an American engineering and robotics design company founded in 1992 as a spin-off from the Massachusetts Institute of Technology. The company is best known for the development of BigDog, a quadruped robot designed for the U.S. military. Boston Dynamics has also developed a number of other robots, including Spot, a four-legged robot designed for indoor and outdoor operation, and Atlas, a humanoid robot designed for a variety of search and rescue tasks. In 2013, the company was acquired by Google X, a subsidiary of Alphabet Inc. In 2020, the company was acquired by Hyundai Motor Group. Boston Dynamics is headquartered in Waltham, Massachusetts.
Learn more about Boston Dynamics
Size
300 employees
Industry
Founded
1992

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