Sr. Applied Scientist, Amazon Music - Search Science

About the role

The Amazon Music Search Science team is seeking an experienced Applied Scientist to join a team of experts in the field of machine learning. The role involves using machine learning, deep learning, LLMs, and Agentic AI techniques to create scalable solutions for business problems. The scientist will analyze and extract relevant information from large amounts of Amazon's data to help automate and optimize key processes. They will design, develop, and evaluate 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. They will also research and implement novel machine learning and statistical approaches.

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

Requirements

• 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

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.

Skills

• 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.

Benefits

• Comprehensive benefits including health insurance, medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave