Audio Data Engineer

4 days ago


Stockholm, Stockholm, Sweden Spotify Full time
Job Overview

The Spotify team responsible for building world-class speech technologies focuses on developing personalized voice products at scale.

  • We design and develop large-scale audio data pipelines using frameworks like Google Cloud Platform and Apache Beam.
  • Our machine learning projects power innovative AI experiences, including state-of-the-art text-to-speech models.
  • Collaboration is key – we work with engineers, researchers, product managers, and stakeholders to drive innovation and growth.
  • Delivering high-quality code is essential, as well as sharing knowledge and promoting standard methodologies within the team.
Required Skills
  • Experience with distributed systems such as Hadoop, BigTable, Cassandra, GCP, AWS is necessary.
  • Expertise in building clean datasets for training large-scale machine learning models is a must, with a focus on audio data being preferred.
  • Familiarity with Python or Java-based data processing frameworks like Beam, Dataflow, Crunch, Scalding, Storm, Spark is required.
  • Strong programming abilities in Python are essential, with experience working with Docker and tools like Luigi, Airflow also being beneficial.
  • Quality and agility are key – you should know what it means to ship high-quality code and understand agile software processes.
  • Experience managing data retention policies and developing datasets tailored for training high-performance machine learning models is highly desirable.
  • Proficiency in cleaning, filtering, and evaluating dataset quality, leveraging both pre-trained and in-house machine learning models, is essential.

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