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.
About the Team: The Data Infrastructure & Business Insights (DIBI) team belongs to the Trust & Safety's Automation & Business Insights (ABI) department. We specialize in defining operational metrics, building scalable data infrastructure, delivering insights-driven performance reporting, and conducting cross-LoB business analysis. Our ultimate goal is to empower global moderation operations to thrive with quality, efficiency, and sustainability.
- Support the planning and execution of AI automation initiatives that improve the efficiency, quality, and scalability of Trust & Safety operations.
- Assist in designing, testing, and refining prompts for LLM-powered workflows and AI agent use cases.
- Analyze operational and AI model performance data, including metrics such as precision, recall, leakage, overkill, and human review quality, to identify improvement opportunities.
- Help evaluate prompt quality, business rules, and automation logic through experimentation and data analysis.
- Build dashboards, reports, and visualizations to monitor AI adoption, operational efficiency, and automation performance.
- Support pilot programs and A/B testing for new AI capabilities and summarize findings for stakeholders.
- Collaborate with Product, Engineering, and Operations teams to gather requirements and coordinate project activities.
- Document workflows, experiment results, best practices, and process improvements to support knowledge sharing across teams.
- Research emerging trends in Generative AI, AI agents, and operational automation to identify opportunities for future innovation.
Minimum Qualifications
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, Engineering, Business Analytics, or a related field.
- Strong analytical and problem-solving skills with the ability to interpret data and generate actionable insights.
- Excellent communication and collaboration skills with the ability to work effectively in cross-functional teams.
- Ability to manage multiple tasks in a fast-paced environment with strong attention to detail.
- Self-motivated learner with curiosity about AI technologies and operational excellence.
- Demonstrated interest or hands-on experience with Large Language Models (LLMs), Generative AI, AI agents, or Machine Learning applications.
- Familiarity with prompt engineering, prompt evaluation, or AI workflow design through coursework, personal projects, hackathons, or internships.
Preferred Qualifications
- Experience using APIs, workflow automation tools, or AI development platforms.
- Knowledge of data analysis and visualization tools (e.g., SQL, Excel, Tableau, Power BI, or Python).
- Interest in Trust & Safety, content moderation, risk management, or large-scale online platform operations.
- Exposure to Retrieval-Augmented Generation (RAG), agentic AI frameworks, or AI evaluation frameworks is an advantage.
- Understanding of AI evaluation concepts such as precision, recall, hallucination, leakage, overkill, or model performance metrics is a plus.