Audio Machine Learning Data Engineer
Core
Develop and manage audio datasets and data pipelines to support supervised, unsupervised, and semi-supervised Machine Learning audio applications.
Role type
Senior IC audio machine learning data engineer
Builds
Audio ML data pipelines, datasets, and automated monitoring tools for Tensilica DSP, ARM, and RISC-V platforms
Domain
Consumer hardware audio, machine learning, embedded systems
Deliverable
production ML models
Required skills
audio data expertise, Python, TensorFlow, Keras, data augmentation, data curation, data labeling, data cleaning, statistical diversity analysis, automated tooling
Preferred skills
audio analysis, artifact detection, audio quality measurement protocols, C, SQL, Git
Technologies
Tensilica DSP, ARM, RISC-V, TensorFlow, Keras, Python, C, SQL, Git
Responsibilities
Ensure integrity and quality of audio ML data pipelines and datasets; develop and deploy audio ML models for resource-constrained platforms; design and manage audio data collection, curation, labeling, cleaning, and augmentation pipelines; evaluate and implement scalable data augmentation techniques; establish and maintain high-quality, versioned datasets for training and benchmarking; build automated tools for monitoring data quality and statistical diversity; formulate strategies for continuous dataset improvement
Seniority
Senior, hands-on IC