About
Tune and optimize ML/DL models for production-scale audio deepfake detection Investigate failure cases and implement mitigation strategies for model robustness Drive model iteration for performance across diverse real-world environments
Required qualifications
Master's or PhD in Computer Science, Machine Learning, Signal Processing, or related field Fresh PhD graduate or Master's with 3+ years of industry experience in ML/DL model deployment Strong programming skills in Python and familiarity with ML frameworks (PyTorch, JAX) Solid understanding of audio processing fundamentals and classification metrics Experience with large-scale training and benchmarking pipelines
Languages
- English
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