Applied Scientist I, Alexa Devices, GENIE Science

We are a part of Amazon Alexa Devices organization with the mission “delight customers through contextual and personalized proactive experiences that keep customers informed, engaged, and productive without cognitive burden”.
We are developing an advanced system using Large Language Model (LLM) technologies to deliver engaging, intuitive, and adaptive content recommendations across all Amazon surfaces. We aim to facilitate seamless reasoning and customer experiences, surpassing the capabilities of previous machine learning models. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware speech assistant. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions.

Key job responsibilities
As an Applied Scientist on the team, you will collaborate with other applied scientists and engineers to develop novel algorithms to enable timely, relevant and delightful recommendations and conversations. Your work will directly impact our customers in the form of products and services that make use of various machine learning, deep learning and language model technologies. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in the state of art.

Basic Qualifications

- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field
- Experience programming in Java, C++, Python or related language

Preferred Qualifications

- Experience implementing algorithms using both toolkits and self-developed code
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
- Have publications at top-tier peer-reviewed conferences or journals

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