Software Development Engineer, Ads Analytics & Insights-Fixed

Amazon Ads works with hundreds of thousands of advertisers, each on a different journey - some running their first campaign, others expanding into streaming TV or display, some at risk of slowing down. The Sales AI team builds the machine learning products that tell sales teams where each advertiser is on that journey and what will help them grow. Our segmentation platform models how advertisers mature over time, predicts where each is heading, and identifies the actions most likely to move them forward - shaping how Amazon Ads organizes sales coverage and decides which advertisers receive managed support.

We're now evolving segmentation from describing where advertisers are to recommending what sellers should do: personalized, interpretable recommendations delivered directly in the tools sellers already use, with a feedback loop that measures which actions actually drive advertiser growth. You'll design and deliver the ML platform and data pipelines that take models from experimentation to production, deliver predictions and recommendations reliably to sales systems at scale, and help move from monthly batch outputs toward on-demand insights - working closely with applied scientists, data scientists, and product partners at the intersection of ML, large-scale data systems, and sales productivity.

Key job responsibilities

• Design, develop, and operate the ML platform that takes segmentation models from experimentation to production - including feature ingestion, training, batch inference, and model monitoring
• Deliver model outputs - predictions, scores, and recommendations - reliably to downstream sales systems and partner teams, with clear freshness, versioning, and availability guarantees
• Build scalable, automated data pipelines that bring new advertiser and sales engagement signals into the models quickly, with strong data quality checks
• Design and deliver solutions for well-scoped problems where the technical approach isn't yet defined - such as serving predictions on demand or generating explanations for recommendations
• Partner with applied scientists and data scientists to productionize new models, shorten iteration cycles, and make it easy for scientists to ship without heavy engineering support
• Build the instrumentation that captures how sellers use recommendations and what happens next, so the team can measure impact and improve the models
• Deliver your services end to end - testing, deployment, monitoring, operational excellence, and on-call
• Participate in design and code reviews, holding a high bar for quality, security, and reliability
• Mentor teammates and help onboard new engineers

A day in the life Your morning might start with the scientists on your team, reviewing results from a new model experiment and deciding what it takes to get it into production. In the afternoon, you might design a pipeline for new advertiser signals, review a teammate's code, or agree with a partner team on how they'll consume a recommendation dataset. Some days you'll trace a data quality alert to its source and fix it; others you'll prototype on-demand predictions. You'll spend most of your day hands-on in the code, and see your work shape how sellers engage with advertisers.

About the team Sales AI is part of Amazon Ads. We're a team of software engineers, applied scientists, data scientists, and product managers who build the machine learning products behind how Amazon Ads understands advertisers and supports them through sales. Our segmentation models already inform how sales coverage is organized, and we're now extending that work into recommendations that sellers use every day. Engineers and scientists here work as one team: we take ideas from experiment to production together, and we judge success by how our work changes seller actions and advertiser growth - not by model metrics alone. 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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, WA, SEATTLE - 143,700.00 - 194,400.00 USD annually