Driving Scene Quality Analyst (USA)

Role Overview We are seeking a highly analytical and detail-oriented Driving Scene Caption Analyst with strong written English skills and a solid understanding of U.S. road rules and traffic laws. This role sits at the intersection of autonomous driving, scene interpretation, and language precision. You will review short sensor feeds, evaluate LLM-generated reasoning, and refine outputs for accuracy, coherence, and clarity. Success in this role requires sharp judgment, spatial reasoning, and the ability to critically assess AI-generated content against visual evidence. What you will work on: Review 30-second autonomous vehicle sensor feeds and interpret driving scenes from a first-person perspective Evaluate and edit LLM-generated thinking traces for logical consistency and clarity Ground entities and events to scene coordinates and object references Revise driving plans to reflect correct actions, justifications, maneuvers, and speed Identify and remove hallucinated objects or events from AI-generated text Distinguish between actual sensor data and fabricated model outputs Maintain a zero-error standard in safety-critical judgments under time pressure Validate that outputs align with observed trajectory, maneuver, and speed Apply U.S. traffic laws and driving logic to evaluate scenarios Requirements: Experience in roles requiring precise writing and structured analytical thinking Documented driving experience in the U.S. with strong knowledge of traffic laws Professional fluency in English with high clarity and precision Ability to evaluate logical coherence in multi-step reasoning Strong attention to detail and ability to maintain quality under time constraints Nice to have skills: Familiarity with LLM-generated content and common failure modes Understanding of hallucinations, reasoning inconsistencies, and instruction-following errors in AI systems Offer Details: Commitments Required: at least 4 hours per day and upto 30-40 hours per week with 4 hours of overlap with PST. Engagement type: Contractor Engagement Length: 12 weeks Evaluation Process - Shortlisted candidates will be onboarded