Amazon Machine Learning Engineer JP Science Data 

Japan 

237450816

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.
Key job responsibilities
The MLE is accountable for:(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(5) Partner with product managers to shape the technical roadmap for vendor growth tooling at AMZ.

- 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