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About Reality Defender

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.

Roles and Responsibilities

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Build real-time audio pre-processing modules (signal filtering, speech enhancement, and voice activity detection) to feed suitable candidates for deepfake classification.
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Build a unified module that combines the pre-processing steps with end-to-end optimization
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Investigate new feature extraction techniques for generative audio detection
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Develop novel solutions that outperform the state-of-the-art and publish the research
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Collaborate with scientists and engineers across the organization
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About You

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Masters in speech/signal processing, deep learning, or a related field.
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Have 2+ years of programming experience in Python and in building deep learning models with PyTorch.
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Familiar with deep learning research on audio synthesis and classification, e.g. using CNNs, RNNs, autoencoders, and large audio foundation models.
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Understands audio research on signal filtering, speech enhancement, and voice activity detection, preferably with 1+ years of hands-on experience.
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Implemented and/or published peer-reviewed research papers in reputable audio/speech/AI research venues, e.g. InterSpeech, NeurIPS, ICLR
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Team player with a positive attitude and good communication skills.
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Excited about our line of work and can start immediately
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