Manager Applied Science, Amazon Music Machine Learning/Personalization
vor 4 Monaten
You will be managing a cross-functional team of Applied Scientists and (Machine Learning) Engineers, driving innovation in ML/AI models for customer and content understanding that drive key personalization tasks like recommendation, ranking, and experience optimization. You will lead your team in setting up roadmaps, experimentation and development, all the way to bringing new products out to improve the Amazon Music customer experience.
Key job responsibilities
- Lead a group of Applied Scientists, ML Engineers and Software Development Engineers located in Berlin, Germany to deliver innovation and solutions-in-production that utilize ML/AI to solve business and customer problems
- Advance the team's craftsmanship and drive continued scientific innovation as a thought leader and practitioner, also influencing beyond your own team into the entire Personalization org
- Develop the roadmap for your team, in collaboration with other teams in the Personalization org and Music at large; oversee planning, and foster cross-team collaboration to execute on complex projects
- Hire and develop top talent, provide technical and career development guidance to people across the organization
- Leverage industry best practices to establish repeatable applied science practices, principles & processes
- Evangelize state-of-the-art and innovation to the wider Amazon Music org
About the team
The Music Machine Learning & Personalization team in Berlin is responsible for foundational ML/AI infrastructure in Amazon Music; providing ML artifacts that capture customer- and content insights; and key primitives for delivering a personalized customer experience, including ranking, experience optimization. The team works closely with other teams in the US (e.g. Seattle, San Francisco), and has a very vibrant, diverse, international, and multi-cultural atmosphere - like Berlin
BASIC QUALIFICATIONS
- PhD, or Master's degree in Computer Science, Machine Learning, Mathematics or related field-Applied research experience
- Experience in leading scientists or machine learning engineers
- Experience in building machine learning models or developing algorithms for business applications
- Experience programming in Python or related language
PREFERRED QUALIFICATIONS
- Experience building complex software systems, especially involving deep learning, machine learning, that have been successfully delivered to customers- Experience in patents or publications at top-tier peer-reviewed conferences or journals, strong publication record
- Experience with popular deep learning frameworks, including PyTorch
- Experience with learning LLMs and Gen AI, both textual and multi-modal approaches
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