Reality Defender

Computer Vision Intern

New York, NY, US

27 days ago
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Summary

About Reality Defender

Reality Defender provides accurate, multi-modal AI-generated media detection solutions to enable enterprises and governments to identify and prevent fraud, disinformation, and harmful deepfakes in real time. A Y Combinator graduate, Comcast NBCUniversal LIFT Labs alumni, and backed by DCVC, Reality Defender is tdhe first company to pioneer multi-modal and multi-model detection of AI-generated media. Our web app and platform-agnostic API built by our research-forward team ensures that our customers can swiftly and securely mitigate fraud and cybersecurity risks in real time with a frictionless, robust solution.

Youtube: Reality Defender Wins RSA Most Innovative Startup

Why we stand out:

  • Our best-in-class accuracy is derived from our sole, research-backed mission and use of multiple models per modality
  • We can detect AI-generated fraud and disinformation in near- or real time across all modalities including audio, video, image, and text.
  • Our platform is designed for ease of use, featuring a versatile API that integrates seamlessly with any system, an intuitive drag-and-drop web application for quick ad hoc analysis, and platform-agnostic real-time audio detection tailored for call center deployments.
  • We’re privacy first, ensuring the strongest standards of compliance and keeping customer data away from the training of our detection models.

Role and Responsibilities

  • Investigate new methods for generative image/video detection
  • Collaborate with researchers in the team
  • Perform research of deepfake image/video detection
  • Write up results of research for internal reports and submission to academic journals/workshops
  • Independently implement and evaluate ideas on modern deep learning stack - Python, PyTorch, and GPU-enabled cloud compute, like AWS/GCP

About You

  • PhD student in a relevant technical field
  • Experience in computer vision
  • Proficient in Python and in building deep learning models with PyTorch.
  • Published peer-reviewed research papers in reputable computer vision venues, e.g. CVPR, ICCV, NeurIPS
  • Team player with a positive attitude and good communication skills.
  • Excited about our line of work

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