Drive research on improved machine learning models for speech quality • Run computational experiments and report findings • Implement ML models that emulate aspects of human auditory perception • Develop next-gen audio quality models • Independently implement ML training pipelines, models, and evaluation frameworks • Regularly report on project progress, dependencies, and risks to stakeholders • Support research scientists and engineers within the team • Execute on applied coding tasks in support of the teams goals. The role requires independently implementing end-to-end ML pipelines, data preparation, model training, hyperparameter tuning, and evaluation using metrics like Mean Absolute Error (MAE), Pearson correlation, Signal-to-Noise Ratio (SI-DR), PESQ, and STOI.