Software Engineer - ML and Distributed Systems, Amazon Personalize

Amazon
Mountain View, California, USA2026-04-01ONSITE

About the job

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. Amazon Personalize is a deep learning AWS Service that makes it easy for developers to create individualized recommendations for customers. We're building a large-scale machine learning platform and are looking for senior engineers to architect and develop the platform.

Responsibilities

Collaborate with experienced cross-disciplinary Amazonians to conceive, design, and bring innovative products and services to market.

Design and build innovative technologies in a large distributed computing environment and help lead fundamental changes in the industry.

Create solutions to run predictions on distributed systems with exposure to innovative technologies at incredible scale and speed.

Build distributed storage, index, and query systems that are scalable, fault-tolerant, low cost, and easy to manage/use.

Design and code the right solutions starting with broadly defined problems.

Work in an agile environment to deliver high-quality software.

Qualifications

Minimum

3+ years of non-internship professional software development experience

2+ years of non-intternship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

Experience programming with at least one software programming language

Preferred

If you have prior experience in building & scaling large scale systems, ML pipelines, and enjoy extracting maximum performance at every layer of the stack, we should talk.