Applied Scientist, Music - Search Relevance

DescriptionAmazon 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 https://www.amazon.com/music.Amazon Music Search Relevance team is seeking an experienced Applied Scientist who will join a team of experts in the field of machine learning, and work together to break new ground in the world of understanding and classifying different forms of music, and creating interactive experiences to help users find the music they are in the mood for. We work on machine learning problems for music classification, recommender systems, dialogue systems, NLP, and music information retrieval. You'll work in a collaborative environment where you can pursue applied research, with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the experience of Amazon Music customers on Alexa/Echo, mobile, and web.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

A day in the lifeImagine being a part of an agile team where your ideas have the potential toreach millions. Picture working on cutting-edge consumer-facing products, where every single team member is a critical voice in the decision-making process. Envision being able to leverage the resources of a Fortune-500 company within the atmosphere of a start-up. Welcome to Amazon Music, where ideas are born and come to life as Amazon Music Unlimited, Prime Music, and so much more.About the teamEveryone on our team has a meaningful impact on product features, new directions in music streaming, and customer engagement. We are looking fornew team members across a variety of job functions including software engineering/development, marketing, design, ops and more. Come join us aswe make history by launching exciting new projects in the coming year.Our team is focused on building a personalized, curated, and seamless musicexperience. We want to help our customers discover up-and-coming artists, while also having access to their favorite established musicians. We build systems that are distributed on a large scale, spanning our music apps, web player, and voice-forward audio engagement on mobile and Amazon Echo devices, powered by Alexa to support our customer base. Amazon Music offerings are available in countries around the world, and our applications support our mission of delivering music to customers in new and exciting ways that enhance their day-to-day lives.Basic Qualifications

3+ years of building machine learning models for business application experience

PhD, or Master's degree and 6+ years of applied research experience

Experience programming in Java, C, Python or related language

Experience with neural deep learning methods and machine learning

Preferred Qualifications

Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

Experience with large scale distributed systems such as Hadoop, Spark etc.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.