Software Development Engineer, Amazon Music Catalog [MusicIQ]
Amazon.com
Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale.
The ideal candidate is interested in being part of a growing team that is passionate about experimenting and innovating for customers, has a demonstrable track record of success in delivering new features and products, and is excited about having end-to-end ownership of high-impact, high-visibility projects. A commitment to collaboration, proficiency in evaluating alternative solutions, and strong communication skills (with both business and technical partners) are absolute requirements. The role requires having a solid depth of technical knowledge, being well-versed in industry best practices, and possessing attention to details.
Key job responsibilities
Key responsibilities are enhancing core ML Infrastructure for tagging music content and helping improve Music similarity. You will work closely with Research scientists to deploy scalable ML models to production, improving model performance and architecture.
A day in the life
Investigate design approaches, prototype new technologies, and evaluate their technical feasibility, such as Auto ML, real-time ML serving systems.- Collaborate with scientists to design and build data pipelines for processing massive datasets and scaling machine learning models.
Develop and maintain platforms/services for developing, evaluating, and deploying machine learning models used in real-world applications.
About the team
Our team is responsible for enhancing the quality and breadth of metadata within Amazon Music Catalog. Our primary focus is on improving the accuracy and completeness of existing metadata while also enriching it to support advanced voice and visual experiences. We own refinement, augmentation and generation of specialized metadata such as Genre, Era, Mood, and Activity. Additionally, the team is responsible for improving overall "Music IQ" by producing sophisticated knowledge features like semantic audio characteristics and GenAI based audio, thematic, and cultural embeddings to improve Music similarity.
The ideal candidate is interested in being part of a growing team that is passionate about experimenting and innovating for customers, has a demonstrable track record of success in delivering new features and products, and is excited about having end-to-end ownership of high-impact, high-visibility projects. A commitment to collaboration, proficiency in evaluating alternative solutions, and strong communication skills (with both business and technical partners) are absolute requirements. The role requires having a solid depth of technical knowledge, being well-versed in industry best practices, and possessing attention to details.
Key job responsibilities
Key responsibilities are enhancing core ML Infrastructure for tagging music content and helping improve Music similarity. You will work closely with Research scientists to deploy scalable ML models to production, improving model performance and architecture.
A day in the life
Investigate design approaches, prototype new technologies, and evaluate their technical feasibility, such as Auto ML, real-time ML serving systems.- Collaborate with scientists to design and build data pipelines for processing massive datasets and scaling machine learning models.
Develop and maintain platforms/services for developing, evaluating, and deploying machine learning models used in real-world applications.
About the team
Our team is responsible for enhancing the quality and breadth of metadata within Amazon Music Catalog. Our primary focus is on improving the accuracy and completeness of existing metadata while also enriching it to support advanced voice and visual experiences. We own refinement, augmentation and generation of specialized metadata such as Genre, Era, Mood, and Activity. Additionally, the team is responsible for improving overall "Music IQ" by producing sophisticated knowledge features like semantic audio characteristics and GenAI based audio, thematic, and cultural embeddings to improve Music similarity.
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