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Reality Defender

Real-time detection of synthetic media.

AI Red Team Researcher

Applied Machine LearningUpdated on Nov 13
Full-time

About the Job

Requirements

  • At least 4 years of experience in offensive security, adversarial machine learning, AI red teaming, or machine learning engineering with a strong adversarial focus.
  • Hands-on experience generating synthetic media, including voice cloning and text-to-speech, face swap, lip-sync, and diffusion-based image and video tools, in an offensive or research context.
  • Strong Python skills and practical machine learning fluency, such as PyTorch or a similar framework, to build attack tooling, automate testing pipelines, and reason about model failures.
  • Working knowledge of adversarial machine learning techniques, including evasion, adversarial perturbations, compression and post-processing attacks, and data poisoning, and of measuring model robustness.
  • Ability to communicate technical findings as prioritized, actionable guidance for engineers and non-technical audiences.

Responsibilities

  • Run continuous adversarial testing against detection models across audio, video, image, and text; reproduce newly released generative tools and techniques and stress-test them against production models.
  • Build realistic, end-to-end attack simulations that mirror real attacker operations, including cloned voices in call centers, real-time synthetic video in onboarding flows and job interviews, virtual camera and media injection, and coordinated cross-channel impersonation.
  • Build and maintain repeatable red team infrastructure, including test harnesses, attack catalogs, and an evolving adversarial dataset used to validate every model release.
  • Prioritize findings, provide AI scientists and engineers with clear reproduction steps, and verify fixes through regression testing.
  • Track open-source models, commercial tools, research papers, and threat actor tradecraft in generative AI; triage techniques most likely to be weaponized next.
  • Partner with Product to shape roadmap priorities based on red team findings.
  • Support Sales, Marketing, and Solutions Engineering with publishable research and threat briefings for enterprise and government customers.
  • Contribute to adversarial testing of the broader platform, including APIs and integrations, in partnership with Security.
  • Help define ethical guidelines and safe-handling practices for synthetic media used in testing.

Desired Qualifications

  • Background in media forensics, signal processing, speech or audio, or computer vision.
  • Traditional red team or penetration testing experience in cloud, APIs, or web; relevant certifications such as OSCP; or familiarity with AI security tooling such as Garak, PyRIT, or the Adversarial Robustness Toolbox.
  • Published research, conference talks, CVEs, or open-source contributions in adversarial machine learning, deepfakes, or AI security.

About the Company

Reality Defender

Real-time detection of synthetic media.

Reality Defender provides a platform that detects deepfakes and AI-generated media for enterprises, government, and institutions. It offers real-time detection across audio, video, images, and text through a web app and API, enabling integration into workflows such as call centers, secure video meetings, and KYC. The product uses a patented multi-model ensemble to identify AI manipulation without relying on watermarks or prior authentication, delivering risk scores in real time. It differentiates itself with its multi-format, real-time detection approach and proven enterprise deployments, including clients like Visa, Microsoft, NATO, and NBCUniversal, as well as its origins from a nonprofit research project. The company’s goal is to help organizations prevent fraud, disinformation, and security breaches by reliably detecting synthetic media as it appears in live streams and communications.

Company size
51-200
Company stage
Series A
Total funding
$48.1M
Headquarters
New York City, New York
Founded
2018

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