Machine Learning Engineer, JP Science and Data

The JP Retail Science team is looking for a Machine Learning Engineer to expand our efforts in vendor tooling.

To help vendors grow their business, Amazon provides multiple programs such as deals, ads, etc. In this position, you will be expected to support the system for pipelines, models and architecture to evaluate the downstream impact of those programs. The underlying models are a mix of causal and ML. The ideal candidate will have knowledge of at least one of ray, spark or rapidsai framework to accelerate model training. A background in causal inference (e.g. Double ML) is a plus but not required. This is the ideal role if you are excited about leveraging science for tangible business impact.

You will work within an international team of scientists and engineers, all based in Tokyo, Japan. We are a team that thrives on growth, both personal and professional. Engage in academic collaborations, spark innovation in hackathons, and expand your horizons with conference visits.


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 vendor growth tooling at AMZ.

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

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