About the role
Scale is building out one of the largest hybrid human-machine systems. Our self-regulating system automatically trains workers and ensures continuous quality and optimal allocation. We have thousands of human labelers that complete millions of tasks a month, and that comes with a host of interesting technical challenges. From product to systems to infrastructure engineering, we're tackling it all to accelerate the development of AI.
Example Projects:
Use models to estimate the quality of tasks and labelers, and guarantee quality on requests at large scale
Properly route tasks from customers to labelers for low turnaround and high accuracy
Build methods to automatically measure and train labelers and optimally match labelers to tasks based on performance
Create optimized and efficient UI/UX tooling for Scalers to complete hundreds of complex tasks
Build robust machine learning models to automate requests and improve our labelers' efficiency
This role could be a fit if you:
Currently pursuing a degree in a relevant field and are a rising junior
Systems engineering experience with real-time and distributed system architecture
Product engineering experience such as building web apps full-stack, integrating with relevant APIs and services
Experience building systems that process large volumes of data
Experience with Python, React, Node.js and/or MongoDB
About the company
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.
