Music AI Scientist — Scale ML & Recommenders

Amazon Science; Sunnyvale (CA); On-site; USD 172,000 - 222,000; Full time

Job summary

Amazon Science is seeking an experienced Applied Scientist to join the Search Science team and advance machine learning for music understanding, classification, and interactive experiences across Amazon Music and Alexa platforms.

You will work with a team of experts on ML, NLP, and recommender systems, deploying models at scale with large datasets and evaluating impact through A/B testing and customer impact analyses.

Qualifications

• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
• 3+ years of building models for business application experience.
• Experience programming in Java, C++, Python or related language.
• Experience building machine learning models or developing algorithms for business application.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.

Responsibilities

• Use machine learning, deep learning, LLMs and Agentic AI 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 AI 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.

Skills

Java

C++

Python

ML models

Distributed computing

Unix/Linux

Education

PhD or Master’s in CS/CE/ML

Job description

Amazon Science is seeking an experienced Applied Scientist to join the Search Science team and advance machine learning for music understanding, classification, and interactive experiences across Amazon Music and Alexa platforms.

You will work with a team of experts on ML, NLP, and recommender systems, deploying models at scale with large datasets and evaluating impact through A/B testing and customer impact analyses.