Audio Annotation Analyst

**Who We Are** -------------- Pindrop is a cybersecurity company delivering continuous identity verification across voice, video, and digital interactions. Powered by the Pindrop Intelligence Network, our unified trust platform helps enterprises answer three critical questions: **Is this identity synthetic?** Detect AI\-generated and manipulated voice and video. **Is this identity risky?** Identify fraud, suspicious behavior, and other risk signals. **Is this identity known?** Authenticate identities using voice, device, behavioral, and other signals. Pindrop brings this intelligence together across purpose\-built trust engines to help organizations make informed decisions in real time — protecting customers, workforce interactions, and emerging AI\-driven interactions. Pindrop protects billions of high\-risk interactions for enterprises, including leading financial institutions, insurers, and healthcare organizations. Its technology is informed by more than 8 billion real\-world interactions annually and protected by 300\+ patents. Recognized by TIME as one of the 10 Most Influential Software Companies of 2026 and by Inc. for Best in Business for Innovation, Pindrop is backed by leading investors including Andreessen Horowitz, IVP, and CapitalG. ### **What you'll do** As an Audio Annotation Analyst on the Research team, you will review and annotate audio recordings, video content, and associated interaction data to support the development, evaluation, and improvement of Pindrop's fraud detection, authentication, and deepfake detection technologies. Your assignments will span audio and video annotation projects based on evolving Research priorities and team needs. Your primary responsibility will be to produce accurate, consistent, and high\-quality annotations across a variety of Research projects. You will also support targeted investigations by reviewing interactions, identifying anomalies, and documenting observations that help Research Scientists better understand model performance and real\-world customer interactions. *You will…* * Review and annotate audio recordings, video content, and associated interaction data, assigning accurate labels based on project\-specific guidelines and classification criteria. * Apply established classification criteria to identify potential fraud indicators, authentication outcomes, characteristics of human\-generated versus synthetic content, and other attributes relevant to Research projects, including intent recognition when applicable. * Apply annotation guidelines consistently across large datasets, review existing labels for discrepancies, and help maintain high\-quality datasets for model development and evaluation. * Flag interactions that are difficult to classify or fall outside established guidelines, document observations, and collaborate with Research Scientists to resolve edge cases. * Support Research investigations by reviewing audio and video interactions to id