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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.
Reality Defender seeks an Applied Scientist Intern to develop audio processing algorithms for our Generative Audio Detection models. We’re looking for a candidate with a background in both signal processing and deep learning
Build a real-time audio processing module comprising signal filtering and sound detection algorithms to feed suitable input candidates for deepfake classification.
Propose novel end-to-end solutions and publish the research.
Collaborate with scientists and engineers across the organization
Currently enrolled in a PhD program in speech/signal processing, deep learning, or a related field
Implemented and/or published peer-reviewed research papers in reputable
audio/speech research venues such as InterSpeech and ICASSP, or
AI research venues such as NeurIPS and ICLR
Have 1+ years of hands-on experience with audio processing algorithms, e.g. signal filtering, sound classification/detection
Have 1+ years of programming experience in Python and building deep learning models in PyTorch, preferably for audio processing such as HuBERT, AST, and wav2vec
Knowledge of setting up end-to-end pipelines would be a plus.
Team player with a positive attitude and good communication skills
Excited about our line of work and can start immediately