Staff, Robotics ML/Data Engineer

Responsibilities

• Architect end-to-end multimodal data ingestion pipelines that convert egocentric video, teleoperation recordings, and third-party datasets into indexed, queryable, training-ready datasets.
• Design cross-modal validation systems for video, proprioception, force/haptic signals, language annotations, and robot state.
• Orchestrate hand tracking, segmentation, depth estimation, 3D reconstruction, pose tracking, human-to-robot trajectory retargeting, and simulation-in-the-loop validation.
• Implement spatial, temporal, viewpoint, and sensor-noise augmentation for expert trajectories and multimodal learning data.
• Create unified state-action representations across embodiments, coordinate frames, rotation conventions, gripper or hand parameterizations, and sampling rates.
• Build tools for dataset querying, visualization, auditing, clip browsing, trajectory review, and annotation workflows.
• Perform temporal segmentation, metadata and scene-graph extraction, embedding-based retrieval, and language annotation of recordings.
• Use model-failure analyses to develop data curation rules and targeted recollection requests.

Requirements

• M.S. or Ph.D. in Computer Science, Data Engineering, Machine Learning, Robotics, or a related field.
• Deep expertise in Python and extensive experience with PyTorch, including custom dataloaders for multimodal datasets.
• Experience processing force-torque sensor, load-cell, or tactile-array time-series data and aligning it with visual frames.
• Mastery of video-processing pipelines and OpenCV, FFmpeg, and Decord for terabyte-scale video datasets.
• Working knowledge of 3D geometry, coordinate frames and transforms, rotation representations, camera intrinsics and extrinsics, forward and inverse kinematics, and URDF.
• Proven ability to implement programmatic and generative data augmentation for computer vision and time-series data.
• Bonus: experience with Open X-Embodiment, DROID, AgiBot World, EgoDex, or similar robotics datasets or software.
• Bonus: familiarity with SAM-family segmentation, monocular depth, MANO or SMPL hand/body pose estimation, 6-DoF object pose tracking, and point tracking.
• Bonus: familiarity with Ray or Apache Spark for distributed data processing.
• Bonus: experience generating or using synthetic robotic data with Omniverse or MuJoCo.
• Bonus: experience integrating spatial-awareness or tactile representations such as Fourier encoding into visual pipelines.

Benefits

• Competitive compensation and performance-based bonus.
• 99% employer-covered medical benefits.
• Early-stage equity and competitive paid time off.
• Company-wide paid winter break from December 24 through January 2.
• Full-time position located in Houston, Texas or Pensacola, Florida.