Sr. SDE, Trust and Store Integrity Science

The Selling Partner Trust and Store Integritys (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 Amazons 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

- 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

- 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 for more information. If the country/region youre applying in isnt 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 $151300/year in our lowest geographic market up to $261500/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.