Sr. Applied Scientist, Music - Catalog

Position: Sr. Applied Scientist, Amazon Music - Catalog
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 live streams 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

As a Sr. Applied Scientist, you will

- Help shape the scientific direction of the organization by proposing state of the art modeling approaches, driving experimentation, and balancing scientific rigor with execution speed to deliver measurable customer impact.

- Think strategically about the future of GenAI and multimodal AI, identifying opportunities to transform music understanding, curation, and engagement.

- Stay at the forefront of advancements in GenAI, recommendation systems, and large-scale machine learning, driving adoption of new techniques where they create meaningful customer value.

- Collaborate closely with engineers across Music Intelligence, Personalization, Search and other partner teams to support long-term product and CX goals.

- Mentor applied scientists and engineers while actively contributing to the broader science and ML community across Amazon Music.

- Produce clear and concise technical documentation outlining methodologies, design decisions, trade-offs, experiment results, and customer impact.

- Invent and scale innovative AI/ML solutions for complex music intelligence, personalization, metadata quality, and content understanding problems.

- Drive the design of scientifically sophisticated ML systems and platforms, contributing core technical innovation and providing organization-wide architectural guidance.

- Define the long-term science vision and roadmap for Amazon Music AI initiatives, translating customer needs into actionable plans for science and engineering teams.

- Partner closely with engineering and product teams to build and launch scalable AI solutions that improve music discovery, personalization, and customer experience.

- Lead rigorous experimentation and data-driven evaluation, including large-scale A/B testing, to measure and optimize customer impact.

- Communicate complex scientific concepts clearly to technical and business stakeholders, including senior leadership.

- Mentor scientists and engineers, fostering a culture of innovation, technical excellence, and strong customer focus.

About the team

The Amazon Music - Catalog Team develops sophisticated models for understanding music across multiple dimensions: sonic, thematic, cultural, lyrical, etc. This team aims to unify this deep music knowledge that will power intelligent music experiences across Amazon Music. Ultimately, the goal of our team is to delivery a musically credible experience, which will help grow engagement across all customers, but also delight the fans!

Basic Qualifications

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

- 5+ years of building machine learning models for business application experience

- Experience programming in Java, C++, Python or related language

- Domain expertise in either Recommender Systems, Search or Ranking

Preferred Qualifications

- Experience with Catalog Metadata, behavioral segmentation at scale

- Experience with real-time ML systems (online scoring, streaming data, anomaly detection)

- Experience working with large-scale customer data platforms or data lake architectures

- Strong publication track record in top AI/ML Conferences (e.g. Recsys, KDD, ICLR, ICML, NeurIPS, etc.)

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

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  (Use the "Apply for this Job" box below).  for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health…