<div class="content-intro"><h2><strong>Who We Are</strong></h2> <p>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:</p> <p><strong>Is this identity synthetic?</strong> Detect AI-generated and manipulated voice and video.<br><strong>Is this identity risky?</strong> Identify fraud, suspicious behavior, and other risk signals.<br><strong>Is this identity known?</strong> Authenticate identities using voice, device, behavioral, and other signals.</p> <p>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.</p> <p>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.</p> <p>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.</p></div><h3>What you’ll do</h3> <p>Depending on your level and domain expertise, as a Pindrop Research Scientist, you will drive core research initiatives, deliver reproducible experimental results, and help translate machine learning models into real-world product solutions. You may:</p> <ul> <li>Conduct research to develop new functionalities and improve existing technologies across our core domains (Fraud, Voice/Speech, Video, Authentication, and Deepfake Detection).</li> <li>Design, implement, and evaluate deep learning algorithms and ML models tailored to complex datasets.</li> <li>Partner closely with research engineers and engineering teams to transition complex research prototypes into efficient, production-ready systems across cloud or edge environments.</li> <li>Support targeted investigations by analyzing system behavior, identifying detection gaps, and recommending practical improvements for our customers.</li> <li>Participate in cross-functional team meetings, contribute to regular research and code reviews, and publish patents and peer-reviewed papers in top conferences.</li> </ul> <h3>Who you are</h3> <ul> <li>You remain focused, persistent, and scientifically rigorous through multiple experimental iterations, navigating ambiguity in research data, quality, or shifting methodologies.</li> <li>You seamlessly bridge the gap between research and engineering teams. You can explain complex AI/ML concepts with clarity to both technical and non-technical stakeholders.</li> <li>You take individual ownership of assigned research projects and workstreams, making sound technical decisions using available data, theory, and rigorous experimental evidence.</li> <li>You follow through on your commitments, communicate research progress transparently, and maintain the highest standard of technical integrity, documentation, and model reproducibility.</li> <li>You use machine learning frameworks effectively to design, train, and evaluate models, carefully validating outputs and applying sound judgment to balance experimentation speed with robustness, compliance, and model quality.</li> </ul> <h3>Your skill-set</h3> <p>Because this is a general pipeline for all levels, we welcome candidates with a variety of backgrounds. The qualifications we look for across our teams include:</p> <ul> <li>Degree (Master’s or PhD) in a quantitative field (e.g., Computer Science, Mathematics, Engineering, Artificial Intelligence) or equivalent industry research experience.</li> <li>We hire across all levels—from early-career researchers (1-3 years) to highly tenured Senior/Principal Research Scientists (6+ years) focused on deep learning, computer vision, face recognition, generative AI, speech processing, or fraud modeling.</li> <li>Strong programming proficiency in Python and hands-on mastery of modern machine learning frameworks such as PyTorch, TensorFlow, or Keras.</li> <li>A proven track record of successful project delivery, publishing peer-reviewed research, or translating research findings into practical improvements (models, decision systems, or production recommendations).</li> <li>Foundational or expert-level knowledge of biometrics, identity authentication, fraud patterns, audio/video pipelines, or consumer security concepts.</li> </ul> <h3>What’s in it for you</h3> <p>At Pindrop, research sits at the intersection of AI, voice, fraud, identity, and customer experience. You’ll turn real-world interaction data into insights that influence how our products evolve and how we help enterprises make better decisions.</p> <ul> <li>Build expertise in an emerging category: Develop firsthand knowledge of voice intelligence, fraud prevention, authentication, and deepfake detection as these fields continue to evolve.</li> <li>Work with real-world data at meaningful scale: Analyze complex calls, interactions, and behavioral patterns to identify trends, anomalies, and opportunities that matter to customers.</li> <li>Learn from experienced research and cross-functional teams: Partner with Research, Product, Engineering, Fraud Strategy, and Customer Experience leaders to understand how insights bec