Staff, Robotics ML/Data Engineer

Persona AI Inc

Houston (TX)

On-site

USD 140,000 - 180,000

Full time

3 days ago
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Benefits offered by this job

Competitive compensation
Bonus program
Medical benefits (99% employer covered
Equity
PTO
Winter break
Advanced tools access

Job summary

Persona AI Inc in Houston, TX is seeking a Staff Robotics ML/Data Engineer to architect and scale end-to-end robotics data pipelines. You will turn raw egocentric video and sensor streams into high-fidelity training assets for foundation model training, with hands-on, pipeline-focused work to improve data quality and researcher visibility.

The role emphasizes cross-modal validation, multimodal module orchestration, and scalable data ingestion to enable rapid research iterations across multiple

Qualifications

  • MS or PhD in Computer Science, Data Engineering, ML, Robotics, or related field.
  • Deep expertise in Python and PyTorch with multimodal dataloader experience.
  • Experience processing time-series data from sensors with alignment to video.
  • Strong video processing with OpenCV, FFmpeg, and Decord.
  • Solid knowledge of 3D geometry, transforms, URDF, and kinematics.
  • Experience with data augmentation for CV and time-series data.

Responsibilities

  • Develop cross-modal validation systems across video, proprioception, force/torque sensors, and language annotations.
  • Orchestrate multimodal modules for hand tracking, segmentation, depth estimation, 3D reconstruction, and pose tracking.
  • Implement data augmentation to improve model robustness.
  • Create unified state-action representations across embodiments and coordinate frames.
  • Build dataset tooling and audit workflows with visualization and annotation review UIs.
  • Develop end-to-end ingestion pipelines for raw recordings and produce training-ready datasets.

Skills

Python
PyTorch
OpenCV
FFmpeg
Decord
URDF
Ray
Apache Spark
Open X-Embodiment
DROID
AgiBot World
EgoDex
SAM-family
MANO
SMPL
Omniverse
MuJoCo
VLM

Education

MS or PhD in Computer Science or related field

Tools

Open X-Embodiment
DROID
AgiBot World
EgoDex
SAM-family
MANO
SMPL
Omniverse
MuJoCo

Job description

Persona AI Inc is building robotics intelligence from multimodal data. In this Staff, Robotics ML/Data Engineer role (onsite in Houston, TX), you will architect and scale end-to-end robotics data pipelines that convert raw in-the-wild egocentric video and dense sensor streams into high-fidelity training assets for downstream foundation model training. The work is hands-on, pipeline-focused, and designed to improve data quality, validation rigor, and researcher visibility.

What you’ll work on
  • Cross-modal validation systems that confirm agreement across video, proprioception, force/haptic signals, and language annotations, including consistency checks such as reprojection of robot state into the image plane and VLM-assisted verification that instructions match observed behavior.
  • Robust orchestration of multimodal modules for hand tracking, segmentation, depth estimation, 3D reconstruction, and pose tracking. You will also retarget human demonstrations into robot trajectories and run simulation-in-the-loop validation (kinematic feasibility, physics replay, motion-consistency filtering) to keep synthesized data physically grounded.
  • Data augmentation for reliability using spatial transformations, temporal scaling, synthetic viewpoints, and sensor noise injection to expand expert trajectories and improve model robustness.
  • Unified state-action representations across differing embodiments, coordinate frames, rotation conventions, gripper/hand parameterizations, and sampling rates, with per-dimension validity masking and per-source normalization. The goal is adding new robots or sensors via configuration rather than rewrites.
  • Dataset tooling and audit workflows that enable researchers to query, visualize, and audit datasets (clip browsers, trajectory viewers, annotation review UIs). You will translate model-failure analyses into new curation rules and targeted re-collection requests.
  • End-to-end ingestion pipelines that take raw, unstructured recordings (egocentric video, teleoperation sessions, third-party open datasets) and produce indexed, queryable, training-ready datasets. This includes temporal segmentation into action clips, metadata and scene-graph extraction, embedding-based retrieval, and language annotation workflows.
What you bring
  • 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, especially implementing custom dataloaders for multimodal datasets.
  • Experience processing complex time-series data from force-torque (F/T) sensors, load cells, or tactile arrays, with pristine alignment to visual frames.
  • Strong video processing experience with OpenCV, FFmpeg, and Decord, including managing I/O bottlenecks for terabyte-scale video datasets.
  • Solid working knowledge of 3D geometry and robotics data: coordinate frames and transforms, rotation representations, camera intrinsics/extrinsics, forward/inverse kinematics, and URDF.
  • Proven ability to implement programmatic and generative data augmentation for computer vision and time-series data.
Tools and technologies you may use

Python, PyTorch, OpenCV, FFmpeg, Decord, URDF, Ray, Apache Spark, Open X-Embodiment, DROID, AgiBot World, EgoDex, SAM-family, MANO, SMPL, Omniverse, MuJoCo, NVIDIA robotic software stack, VLM.

Benefits
  • Competitive compensation
  • Performance-based bonus
  • 99% employer covered medical benefits
  • Early-stage equity
  • Competitive PTO
  • Company-wide paid winter break between December 24th and January 2nd
  • Full access to advanced tools
Bonus skills
  • Experience with NVIDIA’s robotic software stack (Open X-Embodiment, DROID, AgiBot World, EgoDex, or similar).
  • Comfort composing and evaluating perception modules as part of a pipeline, including segmentation (SAM-family), monocular depth, hand/body pose estimation (MANO/SMPL), and 6-DoF object pose tracking or point tracking.
  • Familiarity with distributed data processing systems such as Ray and Apache Spark for cluster computing.
  • Background using or generating synthetic robotic data via simulation (Omniverse, MuJoCo).
  • Experience integrating spatial awareness or tactile data representations (for example, Fourier encoding) into visual pipelines.

Department: Software. Reports to: Teleoperations Lead. Employment type: Full-Time. Location: Houston, TX or Pensacola FL.

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