 Speech Processing ML Algorithm Engineer

• MS or PhD in a computational science field or 3+ years of experience in the field of ML for speech processing.
• A passion for audio ML research for applied product applications, with a deep understanding of transformers, recurrent and convolutional neural networks, etc.
• Experience designing, training, and evaluating machine learning models for speech enhancement, such as noise suppression, dereverberation, source separation, or echo residual suppression.
• Experience building models that meet low-latency, real-time requirements, including streaming and causal processing, and a clear understanding of the quality, complexity, and latency trade-offs involved.
• Strong grounding in audio and speech signal processing fundamentals, for example STFT analysis/synthesis.
• Proficiency with PyTorch and Bash, including version control, code review, testing, and reproducible experiments.
• A habit of following the state of the art literature closely, with the ability to reproduce, critique, and build on published results.
• Working knowledge of speech quality evaluation, spanning objective metrics (e.g. PESQ, STOI, SI-SDR, DNSMOS) and subjective listening tests, along with the data simulation and augmentation needed to support them.
• Experience applying machine learning to adaptive filter prediction and control, such as echo cancellation, active noise control, or adaptive beamforming, including hybrid classical and learned systems.
• Familiarity with Lightning and Hydra.
• Familiarity with model efficiency techniques such as quantization-aware training or distillation.
• Experience in high-performance cloud computing for model training.
• Open source contributions to a repository using in the ML audio community.

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