• Location
    • Mexico City
  • Date Posted
  • May. 18, 2021
  • Function
  • Engineering QA

The Quality Assurance Specialist role is an entry-level 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. You would be working cross-functionally with Customer Operations, Sales, Product, Supply Ops, and Engineering to drive improvements in quality.

You will:

  • Label machine learning data from customers
  • Complete tasks in a timely manner, meeting SLA deadlines
  • Do post-process audits and write error reports on data and tasks
  • Work in-sync with Supply Managers to meet weekly goals
  • Follow up with Customer Operations in regards to questions about quality
  • Identify and resolve the root cause of low quality and provide feedback to respective teams on product improvements

Ideally, you’d have:

  • Advanced English skills
  • .5 to 3 years of customer-service or general work experience
  • Help create processes and best practices
  • Strong attention to detail
  • Great communication skills to work well with others

Nice to haves:

  • Data labeling experience
  • Previous QA experience
  • You play video games!

About Us:

At Scale, our mission is to accelerate the development of Machine Learning and AI applications across multiple markets. Our first product is a suite of APIs that allow AI teams to generate high-quality ground truth data. Our customers include OpenAI, General Motors, NVIDIA, Pinterest, Airbnb, and many more.

Scale AI is an equal opportunity employer. We aim for every person at Scale to feel like they matter, belong, and can be their authentic selves so they can do their best work. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.