Staff, Robotics ML/Data Engineer
Python
Analytics
Artificial Intelligence
Automation
Big Data
Business Intelligence
Computer Vision Ml
Data
Data & Ai
Data Analysis
Data Analytics
Data Engineer
Data Engineering
Data Pipeline
Data Platform
Data Processing
Data Visualization
Deep Learning
Digital Marketing
Engineer
Engineering
Industrial Automation
Machine Learning
Machine Learning Engineer
Machine Learning Infrastructure
Machine Learning Pipelines
Machine Vision
Mechatronics
Programming
PyTorch
Reporting and Analytics
Robotics
Robotics Ai
Robotics Analytics
Robotics Computer Vision
Robotics Machine Learning
Robotics Simulation
Visual Design
Job Description
Persona AI Inc is hiring a Staff, Robotics ML/Data Engineer to architect and scale multimodal robotics data pipelines for foundation model training.
Responsibilities
- Design cross-modal validation systems that check agreement across video, proprioception, force or haptic signals, and language annotations.
- Run validation approaches such as reprojecting robot state into the image plane to verify video-state consistency.
- Use VLM-assisted checks to confirm instructions align with observed behavior.
- Orchestrate multimodal modules including hand-tracking, segmentation, depth estimation, 3D reconstruction, and pose-tracking.
- Retarget human demonstrations into robot trajectories.
- Apply simulation-in-the-loop validation to ensure physical grounding, including kinematic feasibility, physics replay, and motion-consistency filtering.
- Implement robust data augmentation for expert trajectories using spatial transformations, temporal scaling, synthetic viewpoints, and sensor noise injection.
- Unify state-action representations across embodiments, coordinate frames, rotation conventions, gripper or hand parameterizations, and sampling rates.
- Add per-dimension validity masking and per-source normalization so onboarding a new robot or sensor is configuration-driven rather than a rewrite.
- Build dataset tooling for researchers to query, visualize, and audit data, including clip browsers, trajectory viewers, and annotation review UIs.
- Translate model failure analyses into new curation rules and targeted re-collection requests.
- Architect end-to-end ingestion pipelines from raw recordings such as egocentric video, teleoperation sessions, and third-party open datasets.
- Produce indexed, queryable, training-ready datasets including temporal segmentation into action clips.
- Extract metadata and scene-graph information, support embedding-based retrieval, and implement language annotation workflows.
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 complex time-series data from force-torque (F/T) sensors, load cells, or tactile arrays with precise alignment to visual frames.
- Strong video processing pipeline experience and familiarity with libraries including OpenCV, FFmpeg, and Decord, including managing I/O bottlenecks for terabyte-scale video datasets.
- Working knowledge of 3D geometry and robotics data: coordinate frames and transforms, rotation representations, camera intrinsics and extrinsics, forward and inverse kinematics, and URDF.
- Ability to implement programmatic and generative data augmentation techniques for computer vision and time-series data.
Technologies
- 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, NVIDIA's robotic software stack
- VLM
Bonus Skills
- Experience with NVIDIA’s robotic software stack, including Open X-Embodiment, DROID, AgiBot World, EgoDex, or similar.
- Familiarity with modern perception toolbox workflows as a user: segmentation (SAM-family), monocular depth, hand or body pose estimation (MANO/SMPL), 6-DoF object pose tracking, and point tracking.
- Comfort composing and evaluating these components in a data pipeline without needing to train the models.
- Familiarity with distributed data processing for cluster computing (Ray, Apache Spark).
- Background generating or utilizing synthetic robotic data via simulation (Omniverse, MuJoCo).
- Experience integrating spatial awareness or tactile data representations (for example, Fourier encoding) into visual pipelines.
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
Job Details
- Job Title: Staff, Robotics ML/Data Engineer
- Department: Software
- Reports To: Teleoperations Lead
- Employment Type: Full-Time
- Location: Houston, TX (onsite); Houston, TX or Pensacola FL