Amazon Applied Scientist Enterprise Engineering 

United States, Washington, Seattle 

603088650

DescriptionKey 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 agent systems based on a rich set of structured and unstructured contextual signals
- Innovate new methods for 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- Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports
Basic Qualifications
- 5+ years of building machine learning models for business application experience
- PhD, or Master's degree and 5+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learningPreferred Qualifications
- Experience using spark and distributed computing, for big data engineering.
- 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 and knowledge graphs

- 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 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 using Unix/Linux
- Experience in professional software development