Alexa International Tech (AIT) team is looking for a passionate talented and inventive Applied Scientist to help build industryleading technology with Large Language Models (LLMs) and multimodal systems requiring strong deep learning and generative models knowledge.
Key job responsibilities
As an Applied Scientist with the AIT team you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with LLMs. Your work will directly impact our international customers in the form of products and services that make use of digital assistance technology. You will leverage Amazons heterogeneous data sources unique but diverse international customer nuances and largescale computing resources to accelerate advances in voice domain in multimodal setup.
The ideal candidate possesses a solid understanding of machine learning fundamentals and a passion for pushing boundaries in this vast and quickly evolving field. They thrive in fastpaced environments to tackle complex challenges and excel at swiftly delivering impactful solutions while iterating based on user feedback.
A day in the life
Analyze understand and model customer behavior and the customer experience based on large scale data. Especially showing passion towards solving for international customercentric challenges.
Build novel online & offline evaluation metrics an methodologies for personal digital assistants and customer scenarios on multimodal devices.
innovate and deliver deep learning based innovation across lifecycle such as policybased learning international customer specific model performance tuning.
Quickly experiment and setup experimentation framework for agile model and data analysis or A/B testing
Contribute through industry first research to drive the innovation forward.
3 years of building models for business application experience
PhD or Masters degree and 4 years of CS CE ML or related field experience
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 highperformance computing
Experience using Unix/Linux
Experience in professional software development
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