Amazon's Selection Monitoring team is at the forefront of maintaining comprehensive awareness of all products worldwide. This role combines software engineering expertise with cutting-edge AI/ML technologies to build and maintain the most comprehensive and accurate universal product database. As a Software Dev Engineer II, you'll work on innovative solutions for data mapping, machine learning integrations, and natural language processing to improve product data quality and discover new relationships between products globally.
The position offers an exciting opportunity to work with large-scale data challenges while leveraging modern technologies including LLM integrations and machine learning. You'll be responsible for designing and implementing cost-effective solutions that provide both scale and low-latency performance. The role involves end-to-end ownership of features from prototype to production, including the productionization of gen-AI integrations.
Working in the Selection Addition team, you'll collaborate with fellow engineers and stakeholders to deliver technical capabilities that close selection gaps and improve customer experience for sellers, vendors, and shoppers. The team owns critical data transformation workflows and contributes to datasets used by user experience teams across Amazon.
This is an excellent opportunity for engineers passionate about big data, machine learning, and building scalable solutions. You'll be part of a team that directly impacts Amazon's product catalog and selection strategy while working with cutting-edge technologies. The role offers competitive compensation, comprehensive benefits, and the chance to work on challenging problems at global scale.
The position requires participation in regular engineering ceremonies including design reviews, sprint planning, and standups. You'll also be responsible for on-call duties to ensure operational excellence of launched capabilities. This balance of development and operational responsibilities creates space for innovation while maintaining system reliability.