Machine Learning Engineer

Join Amazon Ads in Seattle as a Machine Learning Engineer, onsite, with a salary range of USD 143,700 to 194,400 per year, building 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 leveraging Apache Flink, Kinesis, and DynamoDB to process shopper signals at scale (100K+ TPS) with sub-second latency.
• Develop and maintain ML feature generation services that convert raw customer interactions into signals used by prediction models across Amazon Ads.
• Improve the scalability, automation, and efficiency of large-scale training and real-time inference pipelines.
• Build and refine data quality monitoring frameworks, automated alerts, and self-healing mechanisms to sustain 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.
• Participate in system design discussions, propose technical solutions for ambiguous problems, and drive end-to-end implementation with guidance from senior engineers.

Requirements

• At least 2 years of professional, non-internship software development experience.
• Proficiency in at least one programming language.
• Minimum 2 years of design or architecture experience for new and existing systems, including design patterns, reliability, and scaling.
• Background in machine learning, data mining, information retrieval, statistics, or natural language processing.
• Bachelor's degree in computer science or equivalent.
• At least 2 years across the full software development lifecycle, including coding standards, code reviews, version 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 & AD&D insurance
• Supplemental life plans