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XDOF

Data pipelines and annotation for robotics

Humanoid Engineer

Robotics & Autonomous SystemsConfirmed live in the last 24 hours
Full-timeSan Mateo, CA, USAHybrid

About the Job

Requirements

  • A bachelor's degree or above in Mechanical Engineering, Robotics, Electrical Engineering, Computer Science, or a related field.
  • At least 3 years of experience developing robotics systems, ideally with a focus on humanoid or anthropomorphic designs.
  • Strong knowledge of kinematics, dynamics, and robot control, including movement, balance, and manipulation.
  • Hands-on experience with mechatronics, embedded systems, and sensor integration.
  • Proficiency in programming languages commonly used in robotics, such as C++, Python, and ROS.

Responsibilities

  • Design, prototype, and test humanoid robotic systems, including mechanical, electrical, and software components.
  • Collaborate with interdisciplinary teams to define and refine system architecture, functions, and features for humanoid robots.
  • Develop and implement control algorithms for dexterous manipulation, locomotion, and human-robot interaction.
  • Integrate sensors, perception systems, and artificial intelligence modules to enable robust operation in dynamic environments.
  • Perform simulation, validation, and iterative optimization to improve performance, safety, and reliability.
  • Document designs and results, working closely with manufacturing and field support teams to ensure successful deployment.

Desired Qualifications

  • Familiarity with artificial intelligence, machine learning, and perception for robotics applications.

About the Company

XDOF

Data pipelines and annotation for robotics

XDOF builds data pipelines, data-collection tools, and annotation systems that frontier AI labs and robotics companies use to train robots to operate in the physical world. It tackles the data bottleneck in physical AI by combining teleoperation, simulation, and egocentric data collection, then layering in data cleaning, tooling, and annotation to prepare usable datasets. The company differentiates itself through its end-to-end data infrastructure for physical AI, its mix of teleoperation, simulation, and first-person data methods, and its Berkeley-founded background from 2024. Its goal is to enable robots to learn to operate in the real world by providing the pipelines and labels needed for training.

Company size
1-10
Company stage
Series A
Total funding
$78.3M
Headquarters
Berkeley, CA
Founded
2024

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