- St. Louis
- Date Posted
- May. 25, 2021
- Engineering QA
The Data Labeling Quality 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 adaptable. The role will be focused on annotating tasks and delivering high quality by following a variety of instructions. The role will be perfect for individuals who value challenge in their work. You will be working cross-functionally with Supply Ops and Engineering to drive improvements in quality.
- 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
- Identify and resolve the root cause of low quality and provide feedback to respective teams on product improvements
- Must be a US Citizen, and must be able to pass Background Check
- Must be willing and have ability to obtain and maintain a Secret Security Clearance
- Detail oriented and can follow complex instructions
- Ability to work full-time hours (8-hour workdays)
- Ability to work independently, cooperatively, and collaboratively as a team member
- Possession of excellent oral and written skills
- Strong sense of ownership, urgency, and drive
- Ability to handle ambiguity and changing priorities
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, Zoox, Lyft, Pinterest, Airbnb, nuTonomy, 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.