Applied Scientist Intern, Reality Defender

• Currently enrolled in a PhD program with specialization in machine learning/deep learning, natural language processing, and/or speech processing
• 2+ years of experience with training/fine-tuning large models, esp. audio language models, speech foundation models, multi-modal foundation models
• Experience with end-to-end model building pipeline for ML tasks: dataset curation/cleaning, model implementation, benchmarking, and result analysis
• Familiarity with distributed multi-GPU training Prior experience with publications in reputable ML/Audio/NLP research venues, e.g. NeurIPS, Interspeech, ICASSP, ACL, EMNLP

• Explore and conceptualize novel methods to leverage different modalities (e.g., speech, text) for deepfake detection and relevant audio understanding tasks
• Perform fundamental and applied research to advance the current state-of-the-art on audio deepfake detection
• Build models with generalizability to unseen generative methods - Collaborate with scientists and engineers across the organization
• Summarize, publish, and present research findings

Reality Defender was born out of The AI Foundation to help protect the 2020 US Elections from the threat of deepfakes. It officially launched as a company in 2021, based in New York. Today there continues to be a genuine issue where the public cannot decipher what is true or false online due to the existence of easily-created deepfakes.