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At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.
Job Responsibility:
Ship tools to accelerate the growth of new qualified contributors on Scale’s labeling platform
Build methodical fraud-detection systems to remove bad actors and keep Scale’s contributor base safe and trusted
Use models to estimate the quality of tasks and labelers, and guarantee quality on requests at large scale
Devise advanced matching algorithms to match labelers to customers for optimal turnaround and accuracy
Build methods to automatically measure, train, and optimally match labelers to tasks based on performance
Create optimized and efficient UI/UX tooling, in combination with ML algorithms, for 100k+ labelers to complete billions of complex tasks
Develop new AI infrastructure products to visualize, query, and explore Scale data
Create a customer service RAG application that handles 1000s of questions a day
Integrate a cutting-edge ML model that predicts churn with a customer's retention system
Requirements:
A graduation date in Fall 2025 or Spring 2026 with a Bachelor’s degree (or equivalent) in a relevant field (Computer Science, EECS, Computer Engineering, Statistics)
Product engineering experience such as building web apps full-stack, integrating with relevant APIs and services, talking to customers, figuring out ‘what’ to build and then iterating