About the role

Role Overview

Join Reality Defender as a Staff ML Engineer (Audio) to build, tune, and deploy audio deepfake detection deep learning models for real-world client use.

Responsibilities

Design, build, and optimize production-scale ML/DL models for audio deepfake detection.
Ensure robustness, reliability, and performance across diverse real-world test conditions.
Collaborate cross-functionally with Research, Production Engineering, and Customer Success.
Work with clients to understand production environments and define model performance criteria.
Monitor and measure model performance in production using data analytics and AI observability tools.

Requirements

PhD in Computer Science, Machine Learning, Signal Processing, or related field (or equivalent industry experience).
Strong Python programming skills.
Experience building and deploying ML/DL models for AI products.
Familiarity with audio processing fundamentals.
Understanding of classification/detection metrics, including ROC and DET curves and precision/recall trade-offs.
Experience with large-scale training and benchmarking pipelines.
2+ years industry experience building and deploying ML/DL models.

Nice-to-haves

Comfort working EST hours.
Experience in a client-facing or solutions-oriented AI role.
Experience with ML frameworks such as PyTorch and JAX.

About Reality Defender

Reality Defender builds AI-based solutions focused on detecting and mitigating audio deepfakes. The role centers on deploying robust machine learning models in real-world client environments, bridging research and production engineering to ensure reliable performance.