Machine Learning Engineer

Amazon.com Services LLC is seeking a Machine Learning Engineer to help design and deploy near-real-time ML systems that drive ad relevance within Amazon Ads. This onsite role in New York, NY centers on building end-to-end data pipelines, feature generation, and real-time inference at scale, empowering personalized ad experiences.

Location: New York, NY (onsite). Salary: USD 158,100 - 213,800 per year. Minimum experience: 2 years.

Responsibilities

• Architect and maintain near-real-time data ingestion pipelines using Apache Flink, Kinesis, and DynamoDB to process shopper signals at scale (over 100K transactions per second with sub-second latency).
• Create and sustain ML feature-generation services that convert raw user interactions into signals consumed by prediction models across Amazon Ads.
• Improve the scalability, automation, and efficiency of large-scale training and real-time inference systems.
• Develop data quality monitoring frameworks with automated alerts 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, focusing on design patterns, reliability, and scaling.
• Experience in machine learning, data mining, information retrieval, statistics, or natural language processing.

Technologies

• Apache Flink
• Kinesis
• DynamoDB

Benefits

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

A Day in the Life

• Highly analytical: you base decisions on verifiable data, shaping processes, tools, and statistical methods to support rational decision-making.
• Humbitious: driven to improve while remaining humble, using feedback to continually raise the bar.
• Engaged by ambiguity: you tackle new problem spaces with unique constraints, quickly identifying gaps and the right colleagues to involve.