Amazon’s Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. Our systems process billions of products to algorithmically find products not already sold on Amazon and programmatically add them to the Amazon catalog. We apply parallel processing, machine learning and deep learning algorithms to evaluate products and brands in order to identify and prioritize products and brands to be added to Amazon’s catalog. The datasets produced by our team are used by teams across Amazon to improve: product information, search and discoverability, pricing, and delivery experience. Our work involves building state-of-the-art Information Retrieval (IR) systems to mine the web and automatically create structured entities from un-structure/semi-structured data. We constantly stretch the boundaries of large scale distributed systems, Elastic Computing, Big Data, and SOA technologies to tackle challenges at Amazon’s global scale. Come join us in our journey to make everything – and yes, we do mean *everything* – that anyone wants to buy, available on Amazon! Key job responsibilities We are looking for SDEs with strong technical knowledge, established background in engineering large scale software systems, and passion for solving challenging problems. The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from design to coding, testing, and deployment, to achieve results in a fast paced environment. As a member of the team, in this role, you will: - Work with Sr.SDEs and Principal Engineers to drive the technical and architectural vision for Selection Monitoring’s mission-critical control plane systems. - Build scalable, fault-tolerant, and highly available services that underpin our large scale data processing solutions. - Design and develop capabilities for managing data flow across SM systems. - Build features to support automated bootstrapping of systems for handling new domain on-boarding and multi-tenancy use cases. - Build platform capabilities to enable system driven task allocation model for failure and recovery mode scenarios. - Lead and mentor junior engineers, and drive best practices around design, coding, testability, and security.