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Persona is a configurable identity verification platform serving leading companies like Reddit and OpenAI. The platform helps businesses verify individuals and organizations in a digital-first world, addressing the growing challenge of AI-enabled fraud and evolving regulatory requirements.
In this Senior Research Scientist role, you will lead research on open problems in identity verification and fraud prevention. Your work will focus on detecting AI-generated and manipulated images, understanding model performance across diverse populations, and uncovering patterns in attacker behavior. You'll design and execute focused experiments to test new ideas quickly, developing methods to detect emerging fraud attacks and calibrating model confidence with limited labeled data.
You will partner closely with ML and engineering teams to translate research prototypes into production models that protect real customers. A key aspect of this role is publishing your findings at top-tier venues such as CVPR, NeurIPS, and USENIX Security, maintaining active engagement with the research community.
Key responsibilities include:
- Leading research on identity verification and fraud prevention using rigorous experimental design
- Developing detection methods for manipulated documents and AI-generated images
- Evaluating model reliability and fairness across different populations
- Uncovering fraud patterns in verification data and validating signal quality
- Collaborating with engineering teams to productionize research
- Publishing peer-reviewed work at top conferences
Requirements:
- Deep expertise in at least one of: (1) Computer vision (image forensics, face analysis, generative models, representation learning); (2) Mathematics and statistics (probability, statistical inference, optimization, applied mathematics with empirical research experience); or (3) Identity/fraud prevention (identity verification, biometrics, fraud detection, adversarial behavior, security)
- PhD in Computer Science, Machine Learning, Mathematics, Statistics, or related technical field strongly preferred; MS with exceptional research record considered
- Demonstrated record of peer-reviewed publications in relevant conferences or journals with substantive contributions
- Ability to independently lead research, design rigorous experiments, and use findings (including negative results) to guide next steps
- Clear communication skills for explaining experimental design, findings, and limitations to technical and non-technical audiences
Nice to haves:
- Research on deepfakes, presentation attacks, or adversarial robustness
- Experience with noisy, imbalanced real-world data
- Experience shipping ML research to production
