Amazon Japan Store Tech (JST) Science team serves as the core science division of JP Store Tech, with the vision to enable and accelerate the best-in-class CX through state-of-the-art machine learning technologies. This team owns the science vision definition, science roadmap planning, and science solution delivery in key business areas in Japan including Search, Customer Growth and Engagement, Personalization and Delivery.
As an Applied Scientist, you will design, implement and deliver models on Amazon site, helping millions of customers every day to find quickly what they are looking for. You will propose innovation to build ML models trained on terabytes of product and traffic data, which are evaluated using both offline metrics as well as online metrics from A/B testing. You will then integrate these models into the production system that serves customers, closing the loop through data, modeling, application, and customer feedback. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times.
Key job responsibilities
* Invent or adapt new scientific approaches, models or algorithms inspired and driven by customers’ needs and benefits at the project level.
* Analyze data and identify the gaps in existing solutions, and propose innovative science solutions.
* Contribute to research papers that are published at peer-reviewed internal and/or external venues, and
contribute to the wider scientific community.
* Working with teams worldwide on global projects.
About the team
Your benefits include:
* Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers
* The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems with tangible customer impact
* Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Strong hands-on experiences on customizing GAI/LLM solutions for business use cases. Solid knowledge of LLM post-training, Multi-modal and Multi-agent is preferred.
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