Key Responsibilities
- Review and analyze driving scenarios captured from manual miles.
- Apply the Driving Quality Taxonomy to identify driving behaviors such as Hard Brake, Too Fast, Cutting in Front, Failed to Stop, Lane Following Error, etc.
- Apply the System/Simulation Error Taxonomy to flag issues including: No Router, Adjacent to Router, Camera/Hardware Issue, Context Map Error, Scene Cutting Error
- Assign appropriate label confidence levels (High, Moderate, Low) based on the clarity of evidence.
- Accurately differentiate between closely related categories, e.g., Diverting from Route vs. Not Following Route.
- Maintain consistency and quality across large volumes of labeled data.
- Collaborate with Quality Analysts and Project Leads to ensure adherence to annotation guidelines.
- Participate in calibration and feedback sessions to continuously improve labeling accuracy.
Required Skills & Qualifications
- Bachelor’s degree in Engineering, Computer Science, or a related field preferred.
- Prior experience in Autonomous Vehicle (AV), ADAS, or Simulation Data Analysis projects is desirable.
- Strong analytical and observational skills with keen attention to detail.
- Familiarity with data annotation tools and taxonomy-based classification.
- Ability to understand and apply complex labeling guidelines consistently.
- Good communication and reporting skills.
- Comfortable working in a fast-paced, deadline-driven environment.
Pay: From ₹280,000.00 per year
Work Location: In person
