AI Model and Agent Operation Project Intern (Business Integrity) - 2026 Start

Team Introduction Our team is building an intelligent and automated AI Model Operations framework to continuously improve the quality, efficiency, and scalability of Auto Moderation systems. By combining policy operationalization, Data driven insights, model strategy optimization, and AI-powered automation, we enable machine learning models to deliver accurate and consistent moderation decisions at scale.

You will work closely with Policy, Product, Engineering, Data Science, and Machine Learning teams to support the end-to-end life cycle of AI model operations,from policy implementation and performance analysis to strategy optimization and operational automation.

As a Project Intern, you will contribute to impactful short-term projects and gain hands-on experience in a fast-paced, professional environment. This internship offers the opportunity to develop practical skills, apply your knowledge to real-world challenges, and explore your career interests.

Applications are reviewed on a rolling basis, so we encourage you to apply early.

Responsibilities - Translate moderation policies and business requirements into structured, machine-executable rules and operational strategies. - Monitor and analyze key model performance metrics (e.g., Accuracy, Recall, Precision, False Positive Rate) to identify optimization opportunities. - Conduct root cause analysis on false positives, false negatives and edge cases, and propose strategy-driven improvements. - Conduct root cause analysis on false positives, false negatives and edge cases, and propose data- and strategy-driven improvements. - Support model evaluation, Golden Set construction, and strategy validation to improve model quality and consistency. - Explore AI-powered operational automation by leveraging LLMs, AI Agents, and workflow automation to improve analysis, issue diagnosis, and strategy optimization. - Collaborate with cross-functional teams including Policy, Product, Engineering, Machine Learning, and Operations to drive continuous model improvement.