Amazon Applied Scientist Amazon Music Machine Learning/Personalization 

United States, California, San Francisco 

691916537

Key job responsibilities
- Work backwards from customer problems to research and develop novel machine learning solutions for music and podcast recommendations. Through A/B testing and online experiments done hand-in-hand with engineering teams, you'll implement and validate your ideas and solutions.
- Advocate solutions and communicate results, insights and recommendations to stakeholders and partners.
- Produce innovative research on recommender systems that shapes the field and meets the high standards of peer-reviewed publications. You'll cement your team's reputation as thought leaders pioneering new recommenders. Stay current with advancements in the field, adapting latest in literature to build efficient and scalable modelsA day in the life

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in patents or publications at top-tier peer-reviewed conferences or journals

- Experience implementing algorithms using toolkits and self-developed code
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Have knowledge and practical experience in several of the following areas: machine learning, statistics, deep learning, LLMs, NLP, recommendation systems, information retrieval;Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.