Applied Scientist Intern (Audio) at Reality Defender 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

Applied Scientist Intern (Audio) job at Reality Defender. Remote.

About Reality Defender

Reality Defender provides accurate, multi-modal AI-generated media detection solutions to enable enterprises and governments to identify and prevent fraud, disinformation, and harmful deepfakes in real time. A Y Combinator graduate, Comcast NBCUniversal LIFT Labs alumni, and backed by DCVC , Reality Defender is the first company to pioneer multi-modal and multi-model detection of AI-generated media. Our web app and platform-agnostic API built by our research-forward team ensures that our customers can swiftly and securely mitigate fraud and cybersecurity risks in real time with a frictionless, robust solution.

Why we stand out:

• Our best-in-class accuracy is derived from our sole, research-backed mission and use of multiple models per modality

• We can detect AI-generated fraud and disinformation in near- or real time across all modalities including audio, video, image, and text.

• Our platform is designed for ease of use , featuring a versatile API that integrates seamlessly with any system, an intuitive drag-and-drop web application for quick ad hoc analysis, and platform-agnostic real-time audio detection tailored for call center deployments.

• We’re privacy first , ensuring the strongest standards of compliance and keeping customer data away from the training of our detection models.

Role and 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

About You

• 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.

Compensation

$5K – $8K per month

This salary range is reflective of the total compensation offering for this position. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits. Actual compensation will be determined based on various factors, including the candidate's qualifications, skills, relevant experience, and internal equity. Reality Defender is an equal opportunity employer and committed to fostering a diverse and inclusive culture where everyone can excel.