Amazon Applied Scientist 

United States, California, Sunnyvale 

963782982

Key job responsibilities
- Use deep learning, ML and NLP techniques to create scalable solutions for creation and development of language model centric solutions for building personalized assistant systems based on a rich set of structured and unstructured contextual signals
- Innovate new methods for contextual knowledge extraction and information retrieval, using language models in combination with other learning techniques, that allows effective grounding in context providers when considering memory, compute, latency and quality
- Design and execute experiments to evaluate the performance of state-of-the-art algorithms and models, and iterate quickly to improve results
- Think Big on conversational assistant system personalization over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems
- Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- 2+ years of building models for business application 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 popular deep learning frameworks such as MxNet and Tensor Flow.
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Proficient in 2 of these areas: large language models, information retrieval, recommender systems, knowledge graph, and graph neural networks.