Audio Deepfake Research Intern (Remote)

Reality Defender; United States; Remote; USD 55,800 - 89,280; Part time

Benefits offered by this job

Equity

Benefits

Job summary

Reality Defender seeks an Applied Scientist Intern (Audio) to advance research in multimodal deepfake detection and audio understanding. This remote role partners with our research scientists and engineers to develop, fine-tune, and evaluate models that operate across speech, text, and other modalities.

You will contribute to building robust, scalable detection pipelines, publish findings, and help shape a privacy-first platform used by enterprises and governments.

Qualifications

• 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 publications in ML/Audio/NLP venues (e.g., NeurIPS, Interspeech, ICASSP, ACL, EMNLP).

Responsibilities

• 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

Skills

PhD in ML/NLP/Speech

Fine-tuning large models (audio)

End-to-end ML pipeline

Distributed multi-GPU training

Education

PhD program in ML/deep learning/NLP/speech processing

Job description

Reality Defender seeks an Applied Scientist Intern (Audio) to advance research in multimodal deepfake detection and audio understanding. This remote role partners with our research scientists and engineers to develop, fine-tune, and evaluate models that operate across speech, text, and other modalities.

You will contribute to building robust, scalable detection pipelines, publish findings, and help shape a privacy-first platform used by enterprises and governments.