Audio ML Engineer II developing state-of-the-art audio deepfake detection models for Reality Defender. Tuning and deploying models in real-world client environments with a focus on performance and robustness.
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.
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.
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
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