Staff Data Engineer

Résumé du poste:

The Skywalker Sound Development Group is seeking an experienced Data Engineer to specialize in the creation, management, and optimization of data pipelines to support cutting-edge AI/ML research. This is a critical role in preparing high-quality datasets for the training, retraining, and evaluation of machine learning models tailored to immersive and multichannel audio applications.

As a Data Engineer, you will focus on developing robust pipelines for processing complex media datasets, enabling AI/ML researchers to build transformative solutions for speech processing, style transfer, and source separation. Your work will directly contribute to creating innovative soundtrack workflows for global media production.

What You'll Do

• Design, implement, and maintain scalable, automated data pipelines for the ingestion, preprocessing, and transformation of large-scale audio datasets.

• Ensure pipelines support efficient model training and retraining workflows, enabling continuous improvement of AI/ML models.

• Collaborate with AI/ML researchers to define data requirements and integrate feedback to improve data pipeline functionality.

• Develop advanced preprocessing techniques for immersive and multichannel audio formats (e.g., Dolby Atmos, high-order ambisonics).

• Automate data cleaning, normalization, and augmentation processes to prepare datasets for various model architectures, including foundational models and transformers.

• Integrate external datasets and APIs while ensuring compliance with legal and ethical data usage standards.

• Monitor and optimize pipeline performance to handle complex and dynamic data structures effectively.

• Create tools and workflows for annotating, labeling, and curating datasets, including the use of active learning methods.

• Perform exploratory data analysis to uncover trends, validate dataset quality, and identify data gaps.

What We’re Looking For

• Master’s Degree with preference for PhD in Data Engineering/Science, Computer Science, Signal Processing, or a related field.

• 8+years of experience in data engineering or data science with a focus on building pipelines for AI/ML applications.

• Proficiency in Python, with expertise in data manipulation libraries such as Pandas, NumPy, and PyTorch’s data utilities.

• Hands-on experience with audio processing libraries and tools (e.g., Librosa, FFmpeg, SoX) for handling complex audio formats.

• Familiarity with scalable pipeline tools like GitLab, Apache Spark, Airflow, or Luigi, and experience with containerized workflows (Docker, Kubernetes).

• Strong understanding of data pipeline requirements for model training, retraining, and evaluation in iterative research workflows.

• Experience with immersive and multichannel audio formats.

• Knowledge of cloud-based platforms and tools for storage and processing, such as AWS S3, Redshift, or Google BigQuery.

• Strong problem-solving skills, with a proactive mindset for addressing evolving data challenges.

Preferred Qualifications

• Experience integrating data pipelines with AI/ML workflows, including active learning and model retraining.

• Familiarity with audio-specific datasets and metadata management strategies.

• Knowledge of machine learning principles and how data quality impacts model performance.

• Experience with distributed training pipelines and large-scale dataset processing.

• Contributions to open-source projects or published research in the fields of data science or audio processing.

• Experience with visualization tools (e.g., Tableau, Matplotlib) for quality assurance and exploratory data analysis.

• Expertise in designing systems to support AI/ML model monitoring and retraining over time.

The hiring range for this position in Nicasio, CA is $170,500 to $228,600 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.