We are seeking a Machine Learning Engineer to architect and implement end-to-end machine learning systems that scale across Amazon’s largest vendors. In this role, your primary focus will be on combining strong software engineering principles with machine learning expertise to build robust, production-grade ML platforms and pipelines to support the delivery of advanced analytics and machine learning models for our eCommerce partners as a part of Amazon's new generation of Paid Services.
You will work directly with Applied Scientists to productionize ML models, Software Development Engineers to build scalable infrastructure, Data/BI Engineers to implement scalable ML-ready data pipelines, and Product Managers to drive the roadmap and vision for Paid Services. As a member of the team you will also work with vendors, team members, and internal and external partners to give input into the way we work, how we serve customers, and where we invest in future capabilities.
This position is ideal for candidates with a strong background in software engineering and machine learning systems, demonstrated experience in ML lifecycle management and infrastructure development, and a passion for building scalable ML solutions that drive tangible business impact through our vendor partnerships.
Key job responsibilities
The MLE is accountable for:
(1) Work with scientists to design and develop scalable ML infrastructure that supports model training, deployment, and monitoring across hundreds of vendors
(2) Implement efficient data pipeline and architectures that enable automated ML workflows for our eCommerce partners
(3) Build ML debugging and analysis tools to ensure model reliability and performance
(4) Utilizing Amazon systems and tools to effectively work with terabytes of data.
(5) Partner with product managers to shape the technical roadmap for Amazon’s new generation of Paid Services
About the team
In this position, you will be part of the JP Science and Data team, consisting of scientists, business intelligence engineers, data engineers, and machine learning engineers, collaborating with Product Managers and Software Developers worldwide. Our current projects touch on the areas of causal inference, representation learning, anomaly detection, forecasting, LLMs and more. As part of working on Paid Services, you will be exposed to all other projects the team works on: we believe that collaboration is paramount, and working in isolation does not lead to a happy team.
We place strong emphasis on continuous learning through internal mechanisms for our team members to keep on growing their expertise and keep up with the state of the art. Our goal is to be primary science team for vendor solutions in Amazon, worldwide.- 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 programming with at least one software programming language
- Familiar with the life cycle of a ML model. I.e., trained, customized, tuned and validated ML models that are leveraged in a science application.
- Strong understanding of statistics and math- 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
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.
