The Speak team is Spotifies in-house text-to-speech (TTS) team, supporting products like DJ, AI Voice Translation, as well as the development of exciting new unreleased products. We focus on building world class speech technologies that can power the next generation of personalized generative voice products at scale.What You'll DoBuild large-scale speech and audio data pipelines using frameworks like Google Cloud Platform and Apache BeamWork on machine learning projects powering new generative AI experiences and helping to build state-of-the-art text-to-speech modelsLearn and contribute to the teams best practices and techniques for building data pipelines for large scale generative models, including cleaning, filtering, classifying and labellingCollaborate with other engineers, researchers, product managers and stakeholders, taking on learning and leadership opportunities that ariseDeliver scalable, testable, maintainable, and high-quality codeShare knowledge, promote standard methodologies, making your team the best version of itself through mentorship and constructive accountability.Who You AreYou have Data Engineering experience and you know how to work with high-volume, heterogeneous data, preferably with distributed systems such as Hadoop, BigTable, Cassandra, GCP, AWSYou have experience building clean, high quality datasets for training large scale machine learning models, a focus on audio data is preferredYou have experience with one or more higher-level Python or Java based data processing frameworks such as Beam, Dataflow, Crunch, Scalding, Storm, Spark etcYou have strong Python programming abilities. You might have worked with Docker as well as Luigi, Airflow, or similar toolsYou care about quality and you know what it means to ship high quality codeYou have experience managing data retention policiesYou care about agile software processes, data-driven development, reliability, and responsible experimentationYou understand the value of collaboration and partnership within teamsWere You'll BeThis role is located in London, UK or Stockholm, Sweden