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Video Data Reviewer - Egocentric - AI Trainer

Job in Boston, Suffolk County, Massachusetts, 02298, USA
Listing for: Obsidian
Full Time position
Listed on 2026-08-22
Job specializations:
  • IT/Tech
    Video Production, Data Annotation/ AI Labeling
Salary/Wage Range or Industry Benchmark: 25000 - 33000 USD Yearly USD 25000.00 33000.00 YEAR
Job Description & How to Apply Below

About the Role

We are looking for 5 detail-oriented generalists to support a series of short-term projects involving egocentric (first-person) video data
. The engagement will run for approximately 2 weeks
, covering 3 projects
, with each individual project expected to last between 3 days and 1 week
. The first project is expected to begin Monday morning 17th August (PST).

What You'll Do

You will review egocentric video data and complete structured quality-review tasks according to project-specific guidelines. The work requires strong attention to detail, consistency, and the ability to make precise judgments about actions occurring in first-person video.

Project 1:
Action Segment Boundary Review

For the first project, you will review the boundaries of action segments within egocentric videos.

Dataset

  • 50 egocentric videos

  • Approximately 1-2 minutes per video

  • Approximately 38 action segments per video on average

  • Estimated review time: ~30 minutes per video

Responsibilities

  • Review action segments identified within each video

  • Determine whether segment start and end boundaries accurately correspond to the action being performed

  • Adjust or flag incorrect boundaries according to provided guidelines

  • Maintain consistent judgment across a high volume of short action segments

  • Complete assigned videos within the project timeline

Additional egocentric-data projects will follow during the 2-week engagement. Detailed instructions will be provided at the start of each project.

Who We're Looking For

You may be a strong fit if you:

  • Have excellent attention to detail and visual comprehension

  • Can carefully distinguish between closely related actions and moments in video

  • Are comfortable performing structured, repetitive review work while maintaining accuracy

  • Can quickly learn and consistently apply detailed annotation guidelines

  • Have strong written English communication skills

Prior experience with video annotation, data labeling, computer vision datasets, or egocentric video is helpful but not required.

Engagement Details
  • Openings: 5

  • Duration: Approximately 2 weeks

  • Projects: 3 short-term projects

  • Individual project duration: Approximately 3 days to 1 week

  • First project start: Monday morning PST

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