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Amazon Principle Applied Scientist Amazon Store Tech JST 
United States, Washington, Seattle 
93990588

12.06.2024
DESCRIPTION

As a Principle Applied Scientist, you will lead the team to create the science long-term vision and roadmap across multiple business domains. You will lead the 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. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times.Key job responsibilities
* Drive the scientific vision of the teams in your organization and you advise and influence its technical leadership on scientific challenges pertaining to your areas of expertise.* Lead significantly complex science and design reviews, aligning teams across your organization around coherent algorithmic strategies.* Recognized by internal and external peers as a thought leader in your area(s) of scientific expertise. You publish your results at top academic conferences and engage with the academic community.
Your benefits include:* Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goalsSeattle, WA, USA

BASIC QUALIFICATIONS

- 10+ years of building models for business application experience
- PhD, or Master's degree and 10+ 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


PREFERRED QUALIFICATIONS


- Experience with state-of-the-art modeling algorithms such as LLM, generative AI.