Job Information
Amazon Senior Product Manager-Tech, Amazon Music ML & Personalization in Berlin, Germany
Description
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. Learn more at https://www.amazon.com/music.
Our vision at the Music ML and Personalization team is to offer Amazon customers delightful personalized audio experiences by building world class customer and language understanding, content recommendations and experience optimization platforms. As a team, we play multiple roles at Amazon Music - one, we develop ML models, platforms and capabilities, offer them to internal teams, and experiment with them across experiences to improve personalization; two, we invest in building personalized experiences ourselves like playlists (daily mixes, discovery mixes) and recommenders (new releases for you recommender); and three, we incubate state of the art ML and AI technologies like Generative AI and Large Language Models (LLMs) and leverage them to lift many boats.
Key job responsibilities
As a Senior Product Manager for ML & Personalization based in Berlin, you will help our team define and execute a strategy for becoming the world's most personalized audio streaming service. This role will be focused on building customer affinities by understanding listening preferences, and using it to improve how we rank content recommendations offered to customers. You will also lead early use personalization and work with internal teams to enable and empower them to use our tech primitives to drive retention and engagement. You will work with scientists, engineers, program managers, and a variety of cross functional partners to understand their needs, define a clear vision and strategy, make prioritization decisions, invest in the next generation of models and features, and deploy them across experiences to improve personalization.
A day in the life
In the morning, you will run prioritization discussions with your local team, do tech deep dives and help launch experiments. You will do product discovery to understand internal and external customer problems and write think big documents to propose ambitious solutions and ideas. You will lead them through strategy and execution to deliver value for Amazon Music. You will celebrate wins with the team. Often, in the evening, you will interact with internal customers on the west coast or cross-org attend team meetings. You will travel to our SF/Seattle offices to meet partners roughly twice a year.
We are open to hiring candidates to work out of one of the following locations:
Berlin, BE, DEU
Basic Qualifications
Bachelor's degree
Experience owning/driving roadmap strategy and definition
Experience with feature delivery and tradeoffs of a product
Experience contributing to engineering discussions around technology decisions and strategy related to a product
Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning
Experience with end to end product delivery
Experience in technical product management, program management or engineering
Preferred Qualifications
Experience in building and driving adoption of new tools
Experience with technologies like Hadoop, Rules based systems and Machine learning
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