7 hours ago
London, United KingdomIntern
Responsibilities
- Build and ship full-stack products, AI applications, data pipelines, evaluation infrastructure, and internal tooling.
- Develop systems that process large volumes of data and support reliable AI products.
- Create tooling for contributor growth, fraud detection, quality estimation, matching, and large-scale task completion.
- Collaborate with customers and iterate on what to build while maintaining high product and engineering quality.
Requirements
- Graduate in Fall 2027 or Spring 2028 with a bachelor's degree or equivalent in a relevant field such as Computer Science, EECS, Computer Engineering, or Statistics.
- Be available for a Summer 2027 internship beginning in May or June in San Francisco.
- Have product engineering experience, such as building full-stack web applications and integrating APIs and services.
- Have previous Computer Science or Software Engineering internship experience.
- Demonstrate a track record of shipping high-quality products and features.
- Have experience building systems that process large volumes of data.
- Have experience with Python, TypeScript, React, and/or MongoDB.
- Preferred qualifications include hands-on experience with LLMs, evaluations, or agentic systems, plus open source contributions or a portfolio of shipped side projects.
Benefits
- Summer 2027 internship with a May or June start date in San Francisco.
- Interns receive mentorship from experienced engineers and work on real, shipped projects alongside full-time engineering teams.
Tech Stack
Categories
About Scale AI
Scale AI builds data annotation services and AI development tools for enterprises and government agencies, sold as a platform and managed services. Its products include the Scale Generative AI Platform for building and evaluating agents and the Data Engine for collecting, curating, and labeling training data, including RLHF and model evaluation. Founded in 2016 and headquartered in San Francisco, the company is privately held and works across domains from computer vision to LLM applications.