Staff Data Engineer (Audio/ML)

What you'll do

• Design and maintain scalable, automated pipelines for ingesting and preprocessing large-scale audio datasets.
• Develop advanced preprocessing techniques specifically for immersive and multichannel audio formats like Dolby Atmos.
• Automate data cleaning, normalization, and augmentation to prepare datasets for transformer and foundational models.
• Create tools and workflows for annotating, labeling, and curating datasets using active learning methods.
• Perform exploratory data analysis to validate dataset quality and identify gaps in the training data.
• Integrate external datasets and APIs while ensuring compliance with legal and ethical standards.
• Monitor and optimize pipeline performance to handle complex and dynamic audio data structures.

What we're looking for

• Master's degree in Data Engineering, Data Science, Computer Science, Signal Processing, or a related field (PhD preferred).
• 8+ years of experience in data engineering or data science with a focus on building pipelines for AI/ML applications.
• Proficiency in Python and expertise in libraries such as Pandas, NumPy, and PyTorch's data utilities.
• Hands-on experience with audio processing libraries and tools like Librosa, FFmpeg, and SoX.
• Familiarity with scalable pipeline tools including GitLab, Apache Spark, Airflow, or Luigi.
• Experience with containerized workflows using Docker and Kubernetes.
• Knowledge of cloud-based platforms for storage and processing such as AWS S3, Redshift, or Google BigQuery.
• Experience with immersive and multichannel audio formats like Dolby Atmos and high-order ambisonics.