Machine Learning Engineer, Search Experimentation and ML

The Amazon Search Relevance team is seeking a Machine Learning Engineer to join their Search MLOps team, focusing on accelerating ML lifecycle automation and best practices across CDO. This role offers a unique opportunity to work with one of the world's largest product catalogs and impact how millions of customers discover products on Amazon.

The position involves collaborating closely with Senior Software Engineers in CDO and AWS SageMaker team to define ML lifecycle best practices and build pioneering automation features. You'll be working at the intersection of Machine Learning, Software Engineering, and AWS ML architecture, helping to design and implement solutions that operate at Amazon's massive scale.

The role offers exposure to cutting-edge ML technologies and the chance to build production pipelines for the entire ML model lifecycle. Your work will not only benefit Amazon's internal teams but also external AWS customers operating at similar scales. The team's systems and algorithms are crucial for surfacing relevant products while maintaining strict latency constraints.

This is an excellent opportunity for someone passionate about machine learning infrastructure, with strong software engineering principles and an interest in large-scale systems. The position offers competitive compensation, comprehensive benefits, and the chance to work with world-class engineers in a fast-paced, innovative environment.

The ideal candidate should be collaborative, innovative, and excited about working with complex ML systems at scale. You'll be responsible for building scalable infrastructure, developing monitoring tools, and implementing reproducible ML pipelines while maintaining high standards for code quality and documentation.