Annotation Engineer - Data Analyst

Job Locations
IN-TN-Chennai
Job area
IT & Digital
Employment type
Permanent or Fixed Term Contract
Workplace
On-Site
ID
2026-57641

Overview

Carries out the annotation tasks assigned in Xtreme1 and Valeo's in-house tools, accurately and consistently, following Valeo's annotation guidelines and specifications. Quality and steady daily output are the core of the role, and output is expected to grow as the team scales.

 

Work location

Onsite at Valeo's Chennai premises.

Working pattern

5 days per week, Valeo site calendar and hours

Responsibilities

  •  

    Key responsibilities

    • Annotate assigned scenes in Xtreme1 (with Valeo plugins) and Valeo's in-house tools, for example 2D boxes, 3D cuboids, polygons or segmentation, attributes and object tracking across frames.
    • Follow Valeo's annotation guidelines, ontology and specifications precisely.
    • Self-check every scene against a checklist before submitting it to QC.
    • Complete rework on defects raised by QC within the agreed turnaround.
    • Log time, issues and clarifications in the team tracker each day.
    • Take part in training, calibration on gold scenes and the daily stand-up.
    • Raise guideline doubts early through the Technical Lead, rather than guessing.
    • Work towards agreed productivity and quality targets (scenes per day, first-pass acceptance) as they are set after the pilot.
    • 2–3 years of hands-on data annotation or labelling for computer vision or AI projects.
    • Practical experience with at least one of: 2D image annotation (bounding boxes, polygons, segmentation) or 3D point-cloud / LiDAR annotation (cuboids).
    • Strong attention to detail and the ability to follow detailed written guidelines consistently.
    • Ability to sustain focused, repetitive precision work and meet daily targets.
    • Basic Excel and good written English for logging and clarifications.

    Good to have

    • Automotive or ADAS datasets: vehicles, pedestrians, lanes, traffic signs; camera and LiDAR fusion; object tracking.
    • Experience with Xtreme1 or similar tools such as CVAT, BasicAI, Segments.ai, Label Studio or Supervisory.
    • Use of AI-assisted pre-labelling or interpolation features in annotation tools.

    Education: Any graduate, preferably B.E. / B.Tech / B.Sc. (Computer Science, IT, Electronics) or equivalent

     

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