Amazon Music aims to deepen connections between fans, artists, and creators by innovating at the intersection of music and culture. The job is focused on solving customer problems through machine learning solutions for music and podcast recommendations to enhance the global engagement of Amazon Music.
Requirements
- 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 any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
Responsibilities
- Work backwards from customer problems to research and develop novel machine learning solutions for music and podcast recommendations.
- Implement and validate ideas and solutions through A/B testing and online experiments in collaboration with engineering teams.
- Advocate solutions and communicate results, insights, and recommendations to stakeholders and partners.
- Produce innovative research on recommender systems that meets the standards of peer-reviewed publications.
- Stay current with advancements in the field and adapt the latest developments in literature to build efficient and scalable models.
- Lead innovation in AI/ML to shape Amazon Music experiences for millions by developing state-of-the-art models.
- Collaborate with engineers and scientists to guide research and build scalable models across the audio portfolio.
Other
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Collaborate with product managers, applied scientists, and software engineers to deliver meaningful recommendations.
- Work closely with engineering to realize scientific vision.
- Participate in every aspect of the development lifecycle, from idea generation to deployment of advanced models.
- Innovate daily alongside world-class teams to delight customers worldwide through personalization.
