Senior Audio Data Scientist
13 hours ago
About Spotify
Spotify is a leading audio streaming service that has revolutionized the way people discover and enjoy music and podcasts. Our innovative platform has become a hub for creators and listeners alike, offering a vast library of content and unparalleled personalization capabilities.
About the Role
We're seeking a talented Data Engineer Specialist to join our team and help us build cutting-edge speech technologies that power our personalized generative voice products at scale.
Key Responsibilities
- Data Engineering: Design, build, and maintain large-scale speech and audio data pipelines using frameworks like Google Cloud Platform and Apache Beam.
- Machine Learning Projects: Work on machine learning projects powering new generative AI experiences and helping to build state-of-the-art text-to-speech models.
- Data Quality Assurance: Implement robust data quality assurance processes, ensuring high-quality data throughout the pipeline.
- Collaboration and Leadership: Collaborate with cross-functional teams, taking on learning and leadership opportunities that arise.
- Code Quality and Delivery: Deliver high-quality code that meets scalability, testability, and maintainability standards.
- Mentorship and Accountability: Foster a culture of knowledge sharing, promoting standard methodologies and best practices within the team.
Requirements
- Data Engineering Experience: You have experience working with high-volume, heterogeneous data, preferably with distributed systems like Hadoop, BigTable, Cassandra, GCP, AWS.
- AUDIO DATA FOCUS: A strong focus on audio data is preferred.
- Higher-Level Frameworks: Experience building high-quality datasets for training large-scale machine learning models, with a focus on frameworks like Beam, Dataflow, Crunch, Scalding, Storm, Spark.
- Strong Python Skills: Proven Python programming abilities. Familiarity with Docker, Luigi, Airflow, or similar tools is a plus.
- Quality Focus: You prioritize quality and understand the importance of shipping high-quality code.
- Data Retention Policies: Experience managing data retention policies.
- Agile Software Processes: Familiarity with agile software processes, data-driven development, reliability, and responsible experimentation.
- Collaboration: Understanding the value of collaboration and partnership within teams.
- Dataset Development: Experience developing datasets tailored for training high-performance machine learning models.
- Generative Models: Familiarity with generative models or audio-based machine learning applications is highly desirable.
- Dataset Evaluation: Proficiency in cleaning, filtering, and evaluating dataset quality, leveraging both pre-trained and in-house machine learning models.
Work Location and Schedule
This role offers flexibility to work where you work best. For this role, you can be within the UK region as long as we have a work location. The team operates within the GMT time zone for collaboration.
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