Technical Staff Member, Robotics Data

XDOF

. Analyze robotics data across modalities to identify quality issues, including plotting joint velocities, validating camera poses, checking gripper encoder accuracy, and flagging anomalous collection sessions .

Posted 11/2/2026full-timeSan Mateo • California • United StatesLead💰 $180,000 - $250,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in analyzing robotics data, building automated validation pipelines, and designing data formats and schemas. Proficient in Python data skills and experienced with large datasets, ensuring data quality and visualization in robotics applications.

Highest-signal resume keywords

Python Data SkillsData Visualization ToolsStructured Data Formats3D Geometry UnderstandingRobotics Data Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonNumpyPandasMatplotlibPlotlyData ValidationSignal ProcessingSensor FusionTime-Series AnalysisData Quality Metrics

Soft Skills

Problem-SolvingAttention to DetailCollaborationAdaptabilityPassion for Robotics

Tools & Technologies

ProtobufHDF5ROS BagsTeleoperation SystemsMotion Capture

Industry Keywords

RoboticsData QualityData VersioningAnomaly DetectionSpatial Transformations

Tech Stack

Tools & technologies

NumpyPandasPython

About the role

Key responsibilities & impact

Analyze robotics data across modalities to identify quality issues, including plotting joint velocities, validating camera poses, checking gripper encoder accuracy, and flagging anomalous collection sessions
Build automated validation pipelines that run on ingestion and catch problems before data enters the warehouse
Design and document data formats and schemas across collection modalities, ensuring consistency, versioning, and clear understanding by partners and internal researchers
Build data visualization tools and dashboards for team data inspection
Validate cross-modal temporal alignment, including timestamp synchronization, dropped frame detection, and clock drift across camera, joint, and gripper streams
Define quality metrics and thresholds per modality and track data quality as collection scales
Catalog edge cases and failure modes into a shared taxonomy
Work with data collection operators to trace quality issues to systemic or operator-specific root causes

Requirements

What you’ll need

Bachelor’s or master’s degree (or equivalent experience) in robotics, computer science, mechanical engineering, or a related field
Strong Python data skills, including numpy, pandas, and matplotlib or plotly
Comfort working with large, messy datasets
Solid understanding of 3D geometry, coordinate frames, and spatial transformations
Intuition for physical systems and ability to identify anomalies in trajectories or joint velocity plots
Experience designing or working with structured data formats such as protobuf, HDF5, ROS bags, or similar
Hands-on experience with robotics data from a research lab, robotics startup, or manipulation/locomotion project
Experience with teleoperation systems, motion capture, or egocentric data collection
Experience with signal processing, sensor fusion, or time-series analysis
Experience building internal data visualization tools or dashboards for technical teams
Experience with data versioning, lineage tracking, or schema migration in a production setting
Comfort working in 0→1 environments
Passion for robotics and ability to work in a fast-paced environment

Benefits

Comp & perks

Equity
Hybrid work arrangement