About this role

Design and implement end-to-end model pipelines to production across multiple product domains, including ranking, recommendations, search, and personalization
Develop and maintain scalable data pipelines, data quality checks, and model monitoring to ensure reliability, performance, and responsible behavior of ML systems in production
Collaborate with cross-functional partners (product, analytics, engineering) to translate ambiguous business needs into well-scoped ML projects, communicate findings, and influence decision-making with data-driven insights
Use A/B tests and offline/online evaluation frameworks to measure model impact and guide iterative improvement

Bachelor’s degree in Computer Science or a related technical field; or Equivalent related professional experience
5+ years of relevant professional experience
Proficiency in Python and with ML frameworks and libraries for model development, training, and evaluation
Experience working with large-scale datasets, data processing technologies, and feature pipelines to support model training and inference in a service or multi-service environment
Ability to independently scope, execute, and own ML components of a project, including defining metrics, validating results, and partnering with engineering teams to integrate models into production services

Machine Learning Scientist III – Multi-Product AI

Key skills