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.
Example Projects:
- 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
- Previous Product/Software Engineering Internship experience
- Track record of shipping high-quality products and features at scale
- Experience building systems that process large volumes of data
- Experience with Typescript, React, Python and/or MongoDB
