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Applied Scientist II, Music Search
4 weeks ago
Key job responsibilities
- Use machine learning, deep learning, LLMs and NLP techniques to create scalable solutions for business problems
- Analyze and extract relevant information from large amounts of Amazon's data to help automate and optimize key processes
- Design, development and evaluation of highly innovative models for predictive learning
- Work closely with software engineering teams to drive model implementations and new feature creations
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
- Research and implement novel machine learning and statistical approaches
About the team
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 Qualifications
- 2+ years of building models for business application experience
- PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience building machine learning models or developing algorithms for business application
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred Qualifications
- Experience using Unix/Linux
- Experience in professional software development
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
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