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Quality Assurance Specialist

Are you passionate about shaping the future of AI? Join our team as a QA Specialist, where you'll contribute to training cutting-edge AI models. 
 
The Quality Assurance Specialist role is a remote position for individuals who are interested in working in the Artificial Intelligence and Machine Learning industry. We are looking for a candidate who is a self-starter, detail-oriented, and great at multitasking. The role will be focused on monitoring and maintaining the quality of completed tasks. You would be juggling multiple tasks a day, perfect for individuals who value variety and challenge in their work.
 

Responsibilities

  • Label machine-learning data from customers (text, pictures, videos, or 3D models - depending on the available project)
  • Complete tasks in a timely manner, meeting and maintaining quality standards of the project
  • Do post-process audits and write error reports on data and tasks
  • Help create processes and best practices 
  • Identify and resolve the root cause of low quality and provide feedback to respective teams on product improvements

Preferred qualifications:

  • Advanced English skills
  • Good computer skills (you can work flawlessly and fast on a computer)
  • 0.5 to 3 years of customer service or general work experience
  • Availability to work 40 hours per week
  • Strong attention to detail
  • Great communication skills to work well with others
  • You own or have access to a computer to work

Nice to haves:

  • Data labeling experience
  • Previous QA experience
  • You play video games and/or have a Gamer PC

Earnings & Location:

  • Earnings: $125 USD per week, if work meets quality standards.
  • Location: Mexico - Remote (must be authorized to work in Mexico)
  • Duration: Variable depending on project length, flexible hours

We would like to inform you that the job opportunity offered by Remotasks is a freelance relationship, which means that there is no time-determinate contract. 

 

*Base pay is determined by multiple factors, including the area of expertise, years of experience, and skillset needed for the project. Pay rates vary during the project lifecycle. For example, rates for onboarding are lower.

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