Large Scale Data Pipeline Expert
10 hours ago
About the Team
The Speak team is Spotify's in-house text-to-speech (TTS) team, supporting products like DJ and AI Voice Translation, as well as the development of exciting new unreleased products.
About the Role
We're seeking a skilled Senior Audio Data Scientist to help us build world-class speech technologies that power our personalized generative voice products at scale.
Key Responsibilities
- Data Analysis and Science: Analyze and interpret complex data to inform the development of our speech technologies.
- Model Development: Collaborate with cross-functional teams to develop and deploy state-of-the-art text-to-speech models.
- Data Engineering: Design, build, and maintain large-scale speech and audio data pipelines using frameworks like Google Cloud Platform and Apache Beam.
- Collaboration and Leadership: Collaborate with other engineers, researchers, product managers, and stakeholders, 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 Science Experience: You have experience working with complex data sets, 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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