Enterprise Deepfake Detection
Reality Defender is a groundbreaking security platform offering comprehensive deepfake detection. A Y Combinator graduate, Comcast NBCUniversal LIFT Labs alumni, and backed by DCVC, Reality Defender's proactive deepfake and AI-generated content detection technology is developed by a leadership team with over 20 years of experience in applied research at the intersection of machine learning, data science, and cybersecurity.
With models defending against present and future fabrication techniques, Reality Defender is the best way to detect and deter fraudulent text, audio, and visual content, partnering with government agencies and enterprise clients to enhance security and detect fraud.
Investigate new feature extraction and data augmentation techniques for generative audio detection
Build a pre-processing library to support our deepfake detection models.
Develop novel solutions that outperform the state-of-the-art and publish the research
Collaborate with scientists and engineers across the organization
Masters in deep learning, speech/signal processing, or a related field.
Have 2+ years of programming experience in Python and in building deep learning models with PyTorch.
Familiar with deep learning research on audio synthesis and classification, e.g. using CNNs, RNNs, autoencoders, and large audio foundation models.
Understands audio pre-processing methods, e.g. speech enhancement and voice activity detection.
Implemented and/or published peer-reviewed research papers in reputable AI research/audio/speech venues, e.g. CVPR, ICLR, Interspeech
Team player with a positive attitude and good communication skills.
Excited about our line of work and can start immediately
Reality Defender is a rapidly growing technology startup building the future of deepfake detection technology.
You will help create an AI-first state-of-the-art scalable platform that supports multiple AI models processing thousands of user uploaded videos, images and audio files per day in real time.