drjobs Applied Scientist, Amazon Music AI Personalization

Applied Scientist, Amazon Music AI Personalization

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1 Vacancy
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Job Location drjobs

San Francisco, CA - USA

Yearly Salary drjobs

$ 136000 - 223400

Vacancy

1 Vacancy

Job Description

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 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.

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 youll 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. Youll cement your teams reputation as thought leaders pioneering new recommenders. Stay current with advancements in the field adapting latest in literature to build efficient and scalable models

A day in the life
Lead innovation in AI/ML to shape Amazon Music experiences for millions. Develop state of the art models leveraging and advancing the latest developments in machine learning and genAI. Collaborate with talented engineers and scientists to guide research and build scalable models across our audio portfolio - music podcasts live streaming and more. Drive experiments and rapid prototyping leveraging Amazons data at scale. Innovate daily alongside world-class teams to delight customers worldwide through personalization.

About the team
The team is responsible for models that underly all of Amazon Musics recommendations for all content types (music podcasts audiobooks) and sequencing models for algorithmic stations across mobile web and Alexa. You will collaborate with a team of product managers applied scientists and software engineers delivering meaningful recommendations personalized for each of the millions of customers using Amazon Music globally. As a scientist on the team you will be involved in every aspect of the development lifecycle from idea generation and scientific research to development and deployment of advanced models. You will work closely with engineering to realize your scientific vision.

- 3 years of building models for business application experience
- PhD or Masters 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;

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees supervisors and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees supervisors and staff to ensure exceptional customer service; and follow all federal state and local laws and Company policies. Criminal history may have a direct adverse and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above as well as the abilities to adhere to company policies exercise sound judgment effectively manage stress and work safely and respectfully with others exhibit trustworthiness and professionalism and safeguard business operations and the Companys reputation. Pursuant to the Los Angeles County Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the San Francisco Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136000/year in our lowest geographic market up to $223400/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
This position will remain posted until filled. Applicants should apply via our internal or external career site.

Employment Type

Full-Time

About Company

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