7 hours ago
London, United KingdomEntry Level
Responsibilities
- Build custom AI applications and products for public-sector and enterprise customers.
- Develop reinforcement learning and post-training data pipelines for frontier model development.
- Create evaluation infrastructure for measuring model reliability.
- Ship agentic AI applications and tooling that is observable, testable, and safe to deploy.
- Build fraud-detection, matching, contributor-quality, and contributor-growth systems at scale.
- Develop AI infrastructure products and customer-facing RAG applications.
- Talk directly with customers, determine what to build, and iterate on shipped products and features.
Requirements
- Graduate in Fall 2026 or Spring 2027 with a bachelor’s degree or equivalent in a relevant field such as Computer Science, EECS, Computer Engineering, or Statistics.
- Have product engineering experience, such as building full-stack web applications and integrating APIs and services.
- Have previous Product or Software Engineering internship experience.
- Demonstrate a track record of shipping high-quality products and features at scale.
- Have experience building systems that process large volumes of data.
- Have experience with Python, TypeScript, React, and/or MongoDB.
- Preferred: hands-on experience with LLMs, evaluations, or agentic systems through internships, research, or personal projects.
- Preferred: open-source contributions or a portfolio of shipped side projects.
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.