About this role
Developing reinforcement learning pipelines, building evaluation infrastructure, and shipping agentic AI applications form the core daily work for incoming engineers at Scale AI. Contributors build fraud-detection systems, create optimized UI tooling for over 100k platform workers, and develop AI infrastructure products to query large datasets. Interns take ownership of shipped products on the same roadmaps as full-time staff, gaining mentorship while contributing to high-impact machine learning data systems.
Scale AI provides the data and full-stack technologies powering leading frontier models for enterprise and government partners. This internship exists to integrate promising engineering talent into foundational AI development, with many participants later returning for full-time employment. Ideal candidates possess strong product engineering fundamentals, a history of shipping software, and comfort processing large volumes of data.
What you will do
- Build reinforcement learning and post-training data pipelines to support frontier model development.
- Develop evaluation infrastructure that measures model reliability for enterprise and public sector customers.
- Ship agentic AI applications and create the tooling necessary to make them observable, testable, and safe.
- Create fraud-detection systems that remove bad actors and maintain safety across the contributor base.
- Design advanced matching algorithms to pair contributors with customers for optimal turnaround and accuracy.
- Build optimized and efficient UI/UX tooling combined with machine learning algorithms for large-scale users.
- Develop new AI infrastructure products to visualize, query, and explore complex datasets.
What you need
- Graduation date in Fall 2027 or Spring 2028 with a Bachelor's degree or equivalent in Computer Science, EECS, Computer Engineering, Statistics, or a relevant field.
- Availability for a Summer 2027 internship with May or June start dates located in San Francisco.
- Demonstrated product engineering experience spanning full-stack web applications, API integrations, and iteration loops.
- Previous professional or internship experience in computer science or software engineering.
- Proven track record of shipping high-quality products and features.
- Experience building systems that process large volumes of data.
- Familiarity with Python, TypeScript, React, and/or MongoDB.
Nice to have
- Hands-on experience with LLMs, evaluations, or agentic systems from coursework, research, or personal projects
- Open source contributions or a portfolio of shipped side projects
Skills and tech stack
Questions candidates ask
Where is the internship located?
The internship requires in-person availability for a Summer 2027 start in San Francisco, California.
What qualifications do I need to apply?
Candidates must have a graduation date in Fall 2027 or Spring 2028 with a Bachelor's degree or equivalent in a relevant field like Computer Science, EECS, Computer Engineering, or Statistics. Applicants also need product engineering experience, previous software engineering internship experience, and familiarity with Python, TypeScript, React, or MongoDB.
What kind of projects will I work on?
Interns own real, shipped work on full-time engineering roadmaps, which may include building reinforcement learning pipelines, developing evaluation infrastructure, shipping agentic AI applications, or creating fraud-detection systems.
Can I reapply if I am not selected?
There is a 90-day waiting period before candidates can be reconsidered for the same role to ensure a fair and thorough evaluation process.