Amazon Music · 1 week ago
Applied Scientist, Amazon Music - AI Personalization
Seattle, WA
Full-time
Hybrid
Mid, Senior Level
$136K/yr - $223K/yr
3+ years expAmazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. The Applied Scientist will research and develop machine learning solutions for music and podcast recommendations, advocate for solutions, and produce innovative research while collaborating with engineering teams.
Digital MediaMusicMusic Streaming
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 models
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 Amazon's data at scale
Innovate daily alongside world-class teams to delight customers worldwide through personalization
The team is responsible for models that underly Amazon Music’s recommendations content types (music, podcasts, audiobooks), sequencing models for algorithmic stations across mobile, web and Alexa, ranking models for the carousels and Page strategy on Amazon Music surfaces, and Query Understanding for conversational flow and recommendations
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
Qualification
Required
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
Preferred
Experience using Unix/Linux
Experience in professional software development
Benefits
Equity
Sign-on payments
Medical
Financial
Other benefits
Company
Amazon Music
Amazon Music is a music platform and online music store that connects fans, artists, and creators through music, podcasts, and culture. It is a sub-organization of Amazon.
10001+ employees
H1B Sponsorship
Amazon Music has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (22803)
2024 (21175)
2023 (19057)
2022 (24088)
2021 (12233)
2020 (14881)
Funding
Current Stage
Late StageLeadership Team
Emily Hawcroft
Sr. Global Manager - Artist and Label Partnerships
Frankie Yaptinchay
Sr. Project Manager, Audience Development & Creative Partnerships
Recent News
Digital Music News
2026-01-17
GlobeNewswire
2025-12-18
San Francisco Chronicle
2025-12-04
Company data provided by crunchbase