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Senior Research Scientist, Humanoid Manipulation

FieldAI· Engineering – Research
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Boston, MA$150k - $300kFull-timePosted 1mo ago

About the role

Senior Research Scientist role focused on advancing state-of-the-art humanoid manipulation and robotics foundation models, translating research into scalable, real-world robotic systems deployed on physical humanoid robots.

Responsibilities

  • Advance Humanoid Manipulation Research
  • Help lead high-impact research projects in general-purpose humanoid manipulation and loco-manipulation.
  • Develop novel model architectures, learning objectives, action representations, and training methods for large-scale robot learning.
  • Establish strong baselines, evaluation protocols, and benchmarks for manipulation performance and generalization.
  • Advance Robotics Foundation Models
  • Research large-scale VLAs and other multimodal behavior models that connect perception, language, reasoning, and continuous robot action.
  • Develop imitation-learning and reinforcement-learning methods for improving robustness, precision, dexterity, and long-horizon task performance.
  • Investigate model adaptation, temporal abstraction, memory, uncertainty, data efficiency, and compositional skill learning.
  • Study how model performance scales with architecture, data quantity, data quality, task diversity, and embodiment diversity.
  • Develop methods for transferring capabilities across robots while accounting for embodiment-specific sensing and control constraints.
  • Drive Real-World Deployment and Validation
  • Lead research projects from initial hypothesis through large-scale training, deployment, and validation on physical humanoid robots.
  • Design real-world experiments that expose model limitations and measure generalization under realistic environmental variation.
  • Analyze failures at the level of data, representations, policy behavior, perception, and control.
  • Use insights from robot deployments to guide new research questions and model improvements.
  • Demonstrate learned capabilities across dexterous manipulation, bimanual coordination, and loco-manipulation tasks.
  • Translate Research Into Scalable Systems
  • Partner with research engineers to turn new algorithms into reproducible training pipelines and reliable robot capabilities.
  • Help define data-collection strategies, dataset composition, evaluation standards, and model-development priorities.
  • Provide technical leadership across research projects and mentor other researchers and engineers.
  • Communicate findings clearly through internal technical reviews, publications, presentations, and open-source releases where appropriate.
  • Balance longer-term research efforts with advances that support FieldAI’s near-term autonomy roadmap.

Qualifications

  • PhD in Robotics, Computer Science, Machine Learning, Electrical Engineering, Mechanical Engineering, or a closely related field.
  • A strong research record in robot learning, robotic manipulation, reinforcement learning, imitation learning, multimodal learning, or a related area.
  • Demonstrated ability to lead research projects from an initial technical question through rigorous experimental validation.
  • Deep expertise in at least one relevant area, such as foundation models, VLAs, generative policies, reinforcement learning, imitation learning, or multimodal foundation models.
  • Experience training and evaluating modern deep-learning models using PyTorch.
  • Strong understanding of robotic manipulation, including relevant aspects of kinematics, dynamics, control, perception, and planning.
  • Experience deploying and evaluating learning-based methods on physical robotic systems.
  • Strong experimental judgment, including the ability to design informative ablations, baselines, metrics, and evaluation protocols.
  • A track record of publications or equivalent research impact in leading robotics or machine-learning venues.
  • Ability to communicate research ideas clearly and collaborate effectively across research, engineering, systems, and product teams.

Skills

Required:PhD in relevant fieldRobot learning / manipulation / RL / imitation learningPyTorch
Last updated Oct 22, 2026. Interested? Apply on the company site.

About FieldAI

Robot intelligence built for the real-world.

FieldAI is the leader in deploying general-purpose robots in unstructured environments, providing a universal brain that works across many robots, and many tasks.

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