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AI Video Description Track Quality Scorer

Bella Sharma

Contract-to-hire · Job · Chicago

About the role

Streaming platforms are required to provide audio description tracks for blind and low-vision viewers, but many of those tracks are auto-generated and never quality-checked before publishing. Viewers notice, and complaints pile up in support queues. What we have today is a partnership with two major streaming platforms and a large archive of description tracks paired with viewer feedback. What's missing is an automated way to score description quality before publication instead of relying entirely on complaints after the fact. Your role is to build a scoring model that flags low-quality or mistimed description tracks, working with our accessibility QA team to validate flagged cases before they go into production review queues.

Responsibilities

  • Build a quality-scoring model for audio description tracks
  • Validate flagged cases with the accessibility QA team
  • Analyze viewer complaint patterns to inform scoring criteria
  • Maintain the scoring pipeline in production
  • Report quality trends to platform partners quarterly

Requirements

  • 3+ years working with audio or multimodal data
  • Experience with hugging face audio or speech models
  • Comfortable working with accessibility standards
  • Strong data analysis skills in Python

Benefits

  • Remote position with contract-to-hire path
  • Health insurance upon conversion to full-time
  • Flexible working hours
  • Accessibility-focused mission

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Categories

Automation & AI Workflows data science & analytics

Skills

python hugging face pandas

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Job Type

Contract-to-hire

Level

Mid-Level

Language

English

Salary Range

Negotiable / Competitive

AI Expertise

Automation & AI Workflows data science & analytics

Skills

python hugging face pandas

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