Audio ML Engineer II

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Audio ML Engineer II Global Remote | Remote WHO WE ARE. Reality Defender is an award-winning cybersecurity company helping enterprises and governments detect deepfakes and AI-generated media. Utilizing a patented multi-model approach, Reality Defender is robust against the bleeding edge of generative platforms producing video, audio, imagery, and text media. Reality Defender's API-first deepfake detection platform empowers teams and developers alike to identify fraud, disinformation campaigns, and harmful deepfakes in real time. Backed by world class investors including DCVC, Illuminate Financial, Y Combinator, Booz Allen Hamilton, IBM, Accenture, Rackhouse, and Argon VC, Reality Defender works with leading enterprise clients, financial institutions, and governments in order to ensure AI-generated media is not used for malicious purposes. Youtube: Reality Defender Wins RSA Most Innovative Startup https://www.youtube.com/watch?v=TKOZmwyNUNM THE AUDIO ML ENGINEER II ROLE. We are seeking an Audio ML Engineer II to build, tune, and deploy state-of-the-art audio deepfake detection models in real-world client environments. You will be responsible primarily for model tuning and deployment, ensuring robustness, reliability, and performance under diverse real-world test conditions - including adversarial and edge-case scenarios. The role requires deep hands-on expertise in model building, training, and benchmarking. WHAT YOU'LL DO - Tune and optimize ML/DL models for production-scale audio deepfake detection. - Investigate failure cases in the client environment, build custom evaluation frameworks, and implement mitigation strategies for model robustness. - Drive model iteration for performance under a variety of real-world environments, e.g. compression artifacts, noise, telephony, and streaming pipelines. - Present tech

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