- 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
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
- Bachelor's degree in computer science or equivalent
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.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Amazon’s Customer eXperience Impressions (CXI) team is hiring a Software Engineer to develop machine learning-driven decision systems that detect defects in the Amazon shopping experience and recommend interventions. This role requires expertise across the full machine learning lifecycle, including feature engineering, model development, inference optimization, and real-time decisioning. The engineer will work on large-scale data pipelines, recommendation systems, and automated decision frameworks to ensure Amazon acts before friction impacts demand and customer visits.
CXI operates at the intersection of customer experience and supply chain optimization. As part of Supply Chain Optimization Technology (SCOT), the team’s data infrastructure captures signals from every stage of the shopping journey—search, detail page, and repeat purchase interactions—to measure when and why customers hesitate, abandon their carts, etc.
The engineer will build real-time ML pipelines that evaluate these signals, to ensure that interventions happen at the moment they can still recover lost sales. This includes developing and deploying large-scale ML models that detect and rank defects based on severity and intervention confidence, determining when and how Amazon should act.
Key job responsibilities
This engineer will work closely with Scientists to ask research questions about customer behavior, develop models for defect detection and intervention prioritization, and design experiments to validate assumptions. They will integrate machine learning models into high-performance, distributed decision systems, to ensure low-latency execution at Amazon’s scale. Through experimentation and iterative model refinement, they will ensure that interventions improve purchase outcomes while avoiding unnecessary corrections.
Beyond model integration, this role requires expertise in real-time inference optimization and distributed model serving. The engineer will optimize feature stores, build online learning mechanisms, and design architectures that adapt intervention strategies dynamically based on observed outcomes. They will also develop causal inference frameworks to quantify the true impact of delayed or missed interventions, to ensure the system learns from past decisions to improve future accuracy.
This engineer will actively participate in the Amazon ML community, sharing best practices and mentoring software development engineers who have an interest in ML. Their work will directly benefit customers and the business by ensuring Amazon not only detects shopping experience defects but also determines when and how to act with precision. Their contributions will drive real-time corrections, preserving demand and improving customer satisfaction at scale.
This is a highly visible role and will require regular interaction and communication with senior leaders. Excellent written and verbal communication skills is important.
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