Audio Machine Learning Data Engineer

About the role

As an Audio Machine Learning Data Engineer on Logitech's Hardware Audio ML and DSP product team, you will design, build, and maintain audio data pipelines and datasets that power innovative audio experiences across Logitech devices.

Key responsibilities

• Manage and ensure the integrity of audio ML data pipelines, including robust data augmentation for supervised, unsupervised, and semi‑supervised models.
• Collaborate with engineers to develop and deploy audio ML models on resource‑constrained platforms such as Tensilica DSP, ARM, and RISC‑V.
• Design, curate, label, clean, and augment large‑scale audio datasets, maintaining versioned and well‑documented data assets.
• Implement scalable data‑augmentation techniques and automated tools for monitoring data quality and statistical diversity.
• Formulate strategies for continuous improvement of existing datasets and support model validation, benchmarking, and performance tracking.

Required profile

• Minimum 3 years of hands‑on experience with extensive audio datasets, including advanced augmentation and preprocessing for machine learning.
• Strong Python programming skills for building data pipelines and ML model development.
• Proven ability to build scalable data pipelines and use ML frameworks such as TensorFlow or Keras with large, complex datasets.
• Preferred: expert‑level audio analysis, experience with objective and subjective audio quality evaluation, and familiarity with C, SQL, and Git.

Required skills

• Python
• TensorFlow / Keras
• Audio data augmentation and preprocessing
• Data pipeline development
• C programming
• SQL
• Git version control