Amazon music offerings are available in multiple countries, and our applications support our mission of delivering music to customers in a way that enhances their day-to-day lives. We can be found on platforms such as the Amazon Echo, Kindle Fire, iOS, and Android as well as on a mixture of home and auto streaming platforms.
The Amazon Music Catalog team is responsible for persisting, computing, reconciling and vending Music rights and metadata to other teams and services across Amazon. We process hundreds of millions of updates per day and our services serve tens of thousands of requests per secs to all Amazon Music Customers. We own critical platforms that makes access to the Amazon Music Catalog highly available and accessible to every one.
As a research scientist, you will provide machine learning leadership to the team that helps accelerate the business. You will build various data and machine learning models that help us innovate different ways to enhance customer experience.
You will need to be entrepreneurial, wear many hats, and work in a highly collaborative environment. We like to move fast, experiment, iterate and then scale quickly, thoughtfully balancing speed and quality.
· Drive collaborative research and creative problem solving
· Constructively critique peer research and mentor junior scientists and engineers
· Create experiments and prototype implementations of new learning algorithms and prediction techniques
· Collaborate with engineering teams to design and implement software solutions for science problems
· Contribute to progress of the Amazon and broader research communities by producing publications
· PhD or equivalent Master's degree plus 4+ years of research experience in a quantitative filed
· Experience investigating the feasibility of applying scientific principals and concepts to business problems and products
Ph.D. in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field
· 7+ years of practical experience applying ML to solve complex problems in an applied environment
· Significant peer-reviewed scientific contributions in premier journals and conferences
· Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis
· Experience with defining research and development practices in an applied environment
· Proven track record in technically leading and mentoring scientists
· Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts
Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.