Physical AI Data Quality Analyst

Welocalize • San Francisco, CA

1d • Remote

About The Position

We’re hiring a Physical AI Data Quality Analyst to assess collected robotics data using research-defined quality standards. This role is ideal for someone who has high attention to detail, makes logical decisions, catches subtle differences in motion and perception, and can communicate their findings with clarity and precision.

Requirements

• Bachelor’s degree or equivalent work experience
• Strong attention to detail and the ability to apply consistent logic across diverse scenarios
• Comfortable navigating computer-based tools and quickly learning new software
• Patient, quality-focused mindset with the ability to juggle multiple assignments
• Clear written and verbal communication skills
• Reliable, self-motivated work style and a collaborative spirit within a fast-paced environment
• Identifies and documents edge cases to refine review guidelines over time
• 0–2 years in operations/quality coordination or data analysis.
• Organization across multiple small workstreams; attention to detail.
• Clear communication with internal teams, vendors, and PMs.
• Good use of spreadsheets and task boards; basic BI familiarity is a plus.
• Applies SOPs and QA checks consistently; escalates risks early.
• Operates independently day to day in a remote environment.
• Manages small/medium quality workstreams within defined processes.
• Independent in routine decisions; seeks guidance for non-standard items.
• Collaboration with cross-functional teams.

Nice To Haves

• Hands-on experience with robotic, autonomous, or teleoperated systems
• Experience in data annotation, data entry, legal documentation, evaluation, or human-in-the-loop systems
• Exposure to tools and workflows for data validation and audit

Responsibilities

• Review and score full robotics episodes using a standardized quality rubric and apply judgments consistently across high-volume batches
• Evaluate demonstrations against established quality criteria, including task execution, natural movement, visibility, workflow consistency, realistic behavior, and overall usability
• Identify and document failure cases, unsafe behavior, and edge cases with clear written rationale
• Monitor recurring quality trends and surface patterns that suggest gaps in process, tooling, or training
• Collaborate with stakeholders to improve quality standards and review workflows over time
• Meets daily throughput targets while maintaining a high standard of accuracy and attention to detail
• Applies rubric rules across diverse tasks and operators to maintain high data reliability
• Provides specific, actionable written feedback that helps teleoperators improve collection practices
• Communicates early when standards are unclear or outdated and updates quality documentation

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level