Machine Learning Engineer

Join Amazon.com Services LLC in Seattle, WA, as a Machine Learning Engineer on the Amazon Ads team, developing near real time ML systems and infrastructure for ad relevance and real time personalization across Amazon surfaces.

Responsibilities

• Design, build, and operate near real time data ingestion pipelines with Apache Flink, Kinesis, and DynamoDB to process shopper behavioral signals at scale (100K+ TPS, sub-second latency).
• Develop and maintain ML feature generation services that convert raw customer interactions into ML ready signals used by prediction models across Amazon Ads.
• Improve the scalability, automation, and efficiency of large scale training and real time inference systems.
• Build and enhance data quality monitoring, automated alerting, and self healing mechanisms to ensure signal reliability at 99.9%+ availability.
• Collaborate with applied scientists and partner engineering teams to onboard new shopper signals, define feature schemas, and optimize serving latency for real time ad personalization.
• Contribute to system design discussions, propose technical solutions for ambiguous problems, and drive end to end implementation with guidance from senior engineers.

Requirements

• 2+ years of non internship professional software development experience.
• Experience programming in at least one software language.
• 2+ years of design or architecture experience for new and existing systems, including design patterns, reliability, and scaling.
• Experience in machine learning, data mining, information retrieval, statistics, or natural language processing.
• Bachelor's degree in computer science or equivalent.
• 2+ years of full software development lifecycle experience, including coding standards, code reviews, source control, build processes, testing, and operations.

Technologies

• Apache Flink
• Kinesis
• DynamoDB

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance
• 401(k) matching
• Paid time off
• Parental leave
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• Employee Assistance Program (EAP)
• Mental Health Support
• Medical Advice Line
• Basic Life and AD&D insurance
• Supplemental life plans