Applied Scientist II (Audio)

Reality Defender • New York, NY

2d

About The Position

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
The Applied Scientist II (Audio) Role.
We are seeking an Applied Scientist 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.

Requirements

• Master’s or PhD in Computer Science, Machine Learning, Signal Processing, or related field.
• Fresh PhD graduate, or Masters with 3+ years of industry experience building and deploying ML/DL models for AI products.
• Strong programming skills in Python and model ML frameworks (PyTorch, JAX).
• Solid understanding of audio processing fundamentals, classification and detection metrics (ROC, DET curves, precision/recall trade-offs), model robustness and evaluation.
• Experience with large-scale training and benchmarking pipelines, either in an academic or an industry research role.

Responsibilities

• 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 technical findings and model performance insights to internal stakeholders.
• Interface with Product and Engineering teams to build a deep understanding of the production environment and incorporate relevant evaluations for performance assessment.

Benefits

• Healthcare plans with 100% premium coverage for employees and partial coverage available for dependents
• Dental and Vision plans with 100% premium coverage for employees and their dependents
• Short/Long-term disability and life insurance plans with 100% premium coverage for employees
• FSA/HSA and 401k programs
• Equity compensation
• 20 days of PTO per year
• 12 weeks of Parental Leave
• Learning and Development budget
• Monthly wellness benefits
• Annual company-sponsored offsite
• Daily in-office lunch through UberEats
• Commuter benefits
• Remote Fridays
• Happy Hours and other local events

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level