Software Development Engineer, Machine Learning, Personalization & Recommendations Services, Inc.
 Seattle, WA


Job summary

Are you passionate about machine learning? Do you want to drive the innovation behind real-world recommendation systems? Do you want to impact what is shown to Amazon customers across the website by innovating with Amazon scale data? Amazon’s Personalization team is looking for a Software Development Engineer to work on the core website optimization systems for all of Amazon. You will be part of a multidisciplinary team, working on one of the largest scale machine learning systems in the company. You will hone your skills in areas such as deep learning, multi-armed bandits, and reinforcement learning while building scalable industrial systems. As a member of a highly leveraged team of talented engineers and ML scientists, you will have a unique opportunity to help determine what content gets shown to every customer on Amazon.

As a member of the team, you will use machine learning and analytical techniques to create scalable solutions for business problems. You will propose and run live experiments on customers, with opportunities to publish your work. You bring strong thought leadership, great judgment, clear communication skills, and strong track record of delivery. You will play a critical role in ideation for the team. We are building the next generation optimization system that powers the biggest internet retailer on earth, and we hope you will join us!

Key job responsibilities

In this role as a Software Development Engineer you will:

  • Push the boundaries of real-world recommendation and optimization systems
  • Support science, engineering and product development on a scale only seen at Amazon.
  • Obsess over customer needs and satisfaction.
  • Create intellectual property, influence others while demonstrating significant creativity and being vocally self-critical.
  • Architect for growth in the system’s content, use cases, and users.
  • Operate hands-on and implement algorithms and models delivered to production systems.
  • Work with partners to address concerns and incorporate subject matter expertise into our modeling efforts.

A day in the life

The mission of Amazon’s content optimization system is to enable innovation on behalf of internal content providers by making it easy to get the right content in front of customers at the right time. An applied scientist will define product objectives, define relevant signals and use those to train, validate, and deploy models. We operate in a collaborative environment where you will be expected to provide and solicit feedback and help spread knowledge and learnings.

About the team

Amazon’s Content Optimization System team is responsible for tailoring the experience of every customer on Amazon’s most prominent pages, billions of times a day. Utilizing state of the art machine learning techniques, we build highly scalable, real-time systems that determine the content customers see across the Amazon website.

Basic Qualifications

  • 1+ years of experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and current systems.
  • 2+ years of non-internship professional software development experience
  • Programming experience with at least one software programming language.

Preffered Qualifications

· Master's degree in Machine Learning or related field.

· 3+ years of experience in software development.

· Experience working with recommendation and optimization systems.

· Experience writing computationally efficient software for use on large datasets.

· Have an understanding of the mathematics and theory behind machine learning techniques

· Have an understanding of practical considerations that need to be addressed when applying machine learning techniques to customer problems

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit