Role at a glance
- Job function
-
Software Engineering & IT Backend Engineering
- Salary
- Not yet verified Check the description for pay details; an amount or pay period has not been verified.
- Location
- New York, New York, United States
- Work arrangement
- On-site
- Experience
- Basic Qualifications - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - 1+ years of software development engineer or related occupational experience - 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience - 1+ years of Object Oriented Design experience - Experience programming with at least one software programming language Preferred Qualifications - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Education
- Bachelor's degree in computer science or equivalent
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The Off-Search Online Sourcing team builds real-time ad retrieval systems that search hundreds of millions of ads in milliseconds using embedding models and approximate nearest neighbor indexes for Amazon's non-Search surfaces. This Software Development Engineer role designs and delivers low-latency services, model serving infrastructure, and distributed indexing pipelines, and enriches ad candidates with delivery speed, locality, and return signals. The role also launches retrieval models behind A/B experiments and partners with applied scientists to bring them into production.
What You'll Do
- Design and develop high-throughput, low-latency services that retrieve and enrich ad candidates within strict latency budgets across...
- Build and scale model serving infrastructure for real-time embedding inference, partnering with applied scientists to bring new...
- Develop distributed indexing pipelines that build and refresh large approximate nearest neighbor search indexes across hundreds of...
- Deliver real-time fulfillment signals — delivery speed, locality, return eligibility — that improve ad filtering and ranking quality for...
- Launch new retrieval models and indexes behind A/B experiments, analyze results, and use data to decide what ships to production
- Deliver features end to end — from design and code reviews through implementation, deployment, monitoring, and on-call operations
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required
- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 1+ years of software development engineer or related occupational experience
- 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools,...
- 1+ years of Object Oriented Design experience
- Experience programming with at least one software programming language
Preferred
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes,...
- Bachelor's degree in computer science or equivalent
- Experience building low-latency, high-throughput distributed services
- Experience with search or vector retrieval systems, such as Lucene, Elasticsearch or approximate nearest neighbor indexes
- Experience serving machine learning or generative AI models in production
- Experience with large-scale data processing, such as Spark
- Background in advertising technology, recommendation systems or e-commerce platforms
Original job description
Content provided by the employer
Original job description
Content provided by the employer
This is a team that ships fast — rapidly experimenting with new models, indexes, and signals in production through A/B experiments to grow both advertiser results and shopper engagement. You'll partner closely with applied scientists to bring new retrieval models from research into production, and use experimental results to decide what ships.
Key job responsibilities
- Design and develop high-throughput, low-latency services that retrieve and enrich ad candidates within strict latency budgets across Amazon's non-Search surfaces
- Build and scale model serving infrastructure for real-time embedding inference, partnering with applied scientists to bring new retrieval models into production
- Develop distributed indexing pipelines that build and refresh large approximate nearest neighbor search indexes across hundreds of millions of ads
- Deliver real-time fulfillment signals — delivery speed, locality, return eligibility — that improve ad filtering and ranking quality for shoppers
- Launch new retrieval models and indexes behind A/B experiments, analyze results, and use data to decide what ships to production
- Deliver features end to end — from design and code reviews through implementation, deployment, monitoring, and on-call operations
- Improve operational excellence through caching, graceful degradation, monitoring, and root-cause analysis
- Mentor peers through code and design reviews, helping raise the engineering quality bar across the team
A day in the life
On a typical day you might start by reviewing latency dashboards for your retrieval services, then dive into building a new distributed pipeline to refresh a nearest neighbor index. After lunch, you could be partnering with an applied scientist to integrate a new embedding model into the serving path, setting up the A/B experiment framework to measure its impact. Between coding sessions, you'll review pull requests, debug a latency regression, and check on the results of a running experiment to decide whether a new signal improves shopper engagement enough to ship.
About the team
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry-leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace.
The Off-Search Online Sourcing team within SPB builds the real-time systems that choose which ads shoppers see on the Detail Page, Home Page, and other Amazon pages — searching hundreds of millions of ads in milliseconds using embedding models and approximate nearest neighbor indexes, and enriching every candidate with delivery speed, locality, and return signals so shoppers see ads for products that can reach them quickly.
Basic Qualifications
- 3+ years of non-internship professional software development experience- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 1+ years of software development engineer or related occupational experience
- 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
- 1+ years of Object Oriented Design experience
- Experience programming with at least one software programming language
Preferred Qualifications
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience- Bachelor's degree in computer science or equivalent
- Experience building low-latency, high-throughput distributed services
- Experience with search or vector retrieval systems, such as Lucene, Elasticsearch or approximate nearest neighbor indexes
- Experience serving machine learning or generative AI models in production
- Experience with large-scale data processing, such as Spark
- Background in advertising technology, recommendation systems or e-commerce platforms
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 158,100.00 - 213,800.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.