Software Development Engineer, Prime Science

Description

Amazon Prime’s Science organization leads the Research & Development towards innovation for Amazon Prime. Amazon Prime is the backbone of Amazon’s consumer business and aspires to be the world’s most engaging, satisfying, and loved membership program, driving growth and profitability. The program serves over 200 million members across 25 countries and is key to Amazon’s customer growth and engagement. Prime Science innovates in Artificial Intelligence (inc.

Gen AI) and Economics, to develop algorithms and systems for automated marketing, personalization, targeting, and decisioning. Within the engineering group in Prime Science, we develop world class solutions to complex scientific and engineering problems at Amazon scale. You will work alongside world class scientists to build a suite of fully automated, scalable and robust products driven by the engineering systems you build.

As an experienced engineer, you will collaborate with economists, applied scientists and developers across the company to develop, test and deploy services that implement a wide range of econometric and AI models. This requires the use of sophisticated distributed systems, application of advanced statistical techniques and the processing of big data. A successful candidate will have a passion for innovation, interest in advancing technology, and excitement about working with AI in a high-impact business domain.

• Design and build science products that scale to 100's of millions of customers
• Work alongside a multi-disciplinary team to deliver with high quality on hard science problems
• Interface with internal customers to build science products that solve their needs
• Grow more junior engineers and be force multiplier
• Identify operational challenges early in the system and drive operational excellence
• Contribute to and lead the improvements in development processes

You will work to build out scalable AI/ML foundations for the WW Prime team, scaling science across key Prime marketing activities worldwide. You will develop highly available micro services that power real-time decisions for hundreds of millions of Prime customers — our UDS (Unified Decisioning Service) is a tier-1 service handling peak traffic during Prime Day and holiday events with single-digit millisecond latency requirements.

You will build scalable offline systems for large-scale AI/ML training and inference workflows, including model scoring pipelines that process billions of customer-decisions pairs daily.

You will work with AWS technologies on a daily basis including Bedrock, Sage Maker, EMR, Glue, Step Functions, DynamoDB, ECS/Fargate, and Cloud Watch. You'll collaborate closely with applied scientists to product ionize ML models and with partner teams across Acquisition, Retention, Onboarding, Benefits, and Prime CX to deliver customer-facing experiences at Amazon scale.

The Prime Science engineering team, under the Prime Science organization is working to deliver science products that impact 100's of millions customers world wide. We advance the state of the art on science systems to unlock a delightful customer experience. This is a unique opportunity to work in a start up like mode in Amazon on new science.

• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience programming with at least one software programming language

• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor's degree in computer science or equivalent
• 2+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
• Experience in machine learning, data mining, information retrieval, statistics or natural language processing
• Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of…