Alexa International Tech (AIT) team is looking for a passionate, talented, and inventive Applied Scientist to help build industry-leading 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 Amazon’s heterogeneous data sources, unique but diverse international customer nuances and large-scale computing resources to accelerate advances in voice domain in multi-modal 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 fast-paced 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 customer-centric challenges.
· Build novel online & offline evaluation metrics an methodologies for personal digital assistants and customer scenarios, on multi-modal devices.
· innovate and deliver deep learning based innovation across life-cycle such as policy-based 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 Master's 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, high-performance computing- Experience using Unix/Linux
- Experience in professional software development
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