Description The Selling Partner Trust and Store Integrity's (TSI) vision is that bad actors cannot operate in our store while selling partners start and grow their business without fear of disruption, such that customers and selling partners across the globe trust us, and have confidence in the integrity of Amazon’s store. The mission of the TSI Science team is to accelerate and optimize business impact for all TSI programs through innovative, scalable, and impactful science solutions. This includes building efficient capabilities for detecting emerging and ongoing threats from bad actors, driving operational efficiencies through automation, and supporting compliance initiatives in a flexible and scalable manner. We are seeking an experienced Senior Software Development Engineer/Machine Learning Engineer to lead and shape the future of our centralized science infrastructure. This role will bridge the gap between scientific innovation and engineering excellence, creating scalable solutions that empower multiple science teams across the organization. Key job responsibilities • Lead the architectural design and implementation of enterprise-scale machine learning infrastructure and platforms that serve multiple science domains • Drive standardization and consolidation of scientific workflows, reducing redundancy and improving operational efficiency • Partner with science teams to understand domain-specific challenges and translate them into reusable technical solutions • Define and implement engineering best practices for ML operations, including model deployment, monitoring, and maintenance • Influence and guide science teams in adopting engineering rigor while maintaining their ability to innovate • Establish clear boundaries and interfaces between MLE and Science teams, optimizing for team efficiency and delivery speed • Lead cross-functional initiatives to build common infrastructure that scales scientific solutions into production-grade ML products • Mentor junior engineers and scientists in software engineering best practices and ML system design Basic Qualifications - 8+ years of non-internship professional software development experience - 5+ years of programming with at least one software programming language experience - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience as a mentor, tech lead or leading an engineering team Preferred Qualifications - Experience working with state-of-the-art models (e.g. transformers, LLMs) and model tuning, etc. - Knowledge of modern ML platforms and MLOps practices - Background in one or more scientific domains (Computer Science, Engineering, Statistics, Applied Math, etc.) - Experience with cloud platforms (AWS) - Track record of publishing technical papers or contributing to open-source projects 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. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/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.