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Applied Scientist II - Audio at Reality Defender | Remote

Remote Full-time

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Experience Level

Entry Level

Qualifications

QualificationsMaster’s or PhD in Computer Science, Machine Learning, Signal Processing, or a related domain. Fresh PhD graduate or a Master's degree with a minimum of 3 years of relevant industry experience, specifically in building and deploying ML/DL models for AI solutions. Proficiency in machine learning, deep learning, and audio signal processing.

About the job

About Us

Reality Defender is an award-winning cybersecurity firm dedicated to assisting enterprises and government agencies in the detection of deepfakes and AI-generated media. We leverage a patented multi-model methodology that stands resilient against the forefront of generative platforms producing video, audio, images, and text. Our API-first deepfake detection platform empowers teams and developers to uncover fraud, disinformation campaigns, and harmful deepfakes in real time.

Supported by prominent investors such as DCVC, Illuminate Financial, Y Combinator, Booz Allen Hamilton, IBM, Accenture, Rackhouse, and Argon VC, Reality Defender collaborates with esteemed enterprise clients, financial institutions, and governmental organizations to ensure that AI-generated media is not exploited for malicious intents.

YouTube: Reality Defender Wins RSA Most Innovative Startup

The Role: Applied Scientist II - Audio

We are on the lookout for an Applied Scientist II to develop, fine-tune, and deploy cutting-edge audio deepfake detection models in real-world client settings.

Your primary responsibilities will include model tuning and deployment, ensuring robustness, reliability, and performance under a variety of real-world testing conditions, addressing adversarial and edge-case scenarios. This position demands extensive hands-on experience in model building, training, and benchmarking.

Responsibilities

  • Tune and optimize ML/DL models for scalable audio deepfake detection.
  • Analyze failure scenarios in client environments, build custom evaluation frameworks, and implement strategies to enhance model robustness.
  • Guide model iterations to ensure performance across various real-world conditions, such as compression artifacts, noise, telephony, and streaming pipelines.
  • Communicate technical findings and model performance insights to internal stakeholders.
  • Collaborate with Product and Engineering teams to gain a comprehensive understanding of the production environment and incorporate relevant evaluations for performance assessment.

Candidate Profile

  • Master’s or PhD in Computer Science, Machine Learning, Signal Processing, or a related field.
  • Recent PhD graduate or a Master's degree holder with 3+ years of industry experience in building and deploying ML/DL models for AI applications.
  • Strong foundation in machine learning, deep learning, and audio signal processing.

About Reality Defender

Reality Defender is an innovative cybersecurity company focused on detecting deepfakes and AI-generated media, helping enterprises and governments safeguard against malicious uses of technology.

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