Startups · AI

Senior Perception Engineer

XDOF · San Mateo Hybrid · Remote

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About XDOF

Defining motion for autonomous systems. Backed by a16z.

About the role

Design and optimize hand pose estimation pipelines supporting accurate joint angle extraction from teleoperation data collection Build full-body pose estimation systems for motion capture and teleoperation action annotation ground truth generation

What they're looking for

  • Must-Have
  • 5+ years of industry experience in robot perception or computer vision
  • Strong 3D vision fundamentals: stereo and structured-light camera principles, 3D reconstruction
  • Proficiency with SLAM frameworks (ORB-SLAM, VINS-Mono, FastLIO, etc.) or V-SLAM system development experience
  • Hands-on engineering experience with human pose estimation: hand joints (MediaPipe, MANO) or full-body pose (OpenPose, SMPLify, etc.)
  • Proficient in deep learning training frameworks for perception model training, tuning, and evaluation
More about this role

At XDOF, we’re at an inflection point. Frontier labs are racing to build general-purpose robots, and high-quality training data is the bottleneck. We’re building the foundation behind the foundation models – the data collection systems, operational capability, exabyte-scale data warehouse, and software toolchain – to help our partners drive the field forward.

The Perception Algorithm team transforms raw multimodal sensor data into high-quality robot training annotations. You will be deeply involved in the complete loop from data collection to model delivery — sensor calibration, SLAM localization, human pose estimation, perception model training, and embedded deployment. Your work directly determines the quality ceiling of our training data.

Human Pose Estimation

Design and optimize hand pose estimation pipelines supporting accurate joint angle extraction from teleoperation data collection

Build full-body pose estimation systems for motion capture and teleoperation action annotation ground truth generation

Research and apply vision-based pose estimation methods (markerless) to reduce data collection costs

Fuse pose estimation outputs with robot joint angle data to generate...

Read the full posting on XDOF's site ↗

Robotics

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