Applied Scientist II, Amazon Music Catalog
The Amazon Music Catalog team is seeking an experienced Applied Scientist to join a team of experts in machine learning. You will work on understanding and classifying different forms of music and creating interactive experiences to help users find music that suits their mood. We tackle machine learning problems related to music classification, recommender systems, dialogue systems, NLP, and music information retrieval. In this collaborative environment, you can pursue applied research, solve unsolved problems, implement and deploy algorithmic ideas at scale, and evaluate their success through statistically relevant experiments across millions of customers. Your work will directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web.
Key Job Responsibilities
1. Use machine learning, deep learning, LLMs, and NLP techniques to create scalable solutions for business problems.
2. Analyze and extract relevant information from large amounts of Amazon's data to help automate and optimize key processes.
3. Design, develop, and evaluate highly innovative models for predictive learning.
4. Work closely with software engineering teams to drive model implementations and new feature creations.
5. Establish scalable, efficient, automated processes for large-scale data analyses, model development, model validation, and model implementation.
6. 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 exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Learn more at amazon.com/music.
BASIC QUALIFICATIONS
1. 2+ years of building models for business application experience.
2. PhD, or Master's degree and 3+ years of experience in CS, CE, ML, or a related field.
3. Experience with programming or scripting languages like Python, Java, C, or C++.
4. Experience building machine learning models or developing algorithms for business applications.
5. Experience in areas such as algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing.
PREFERRED QUALIFICATIONS
1. Experience using Unix/Linux.
2. Experience in professional software development.
3. Experience in patents or publications at top-tier peer-reviewed conferences or journals.
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