Amazon Research Scientist Enterprise Engineering 

United States, Washington, Seattle 

637731792

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 3+ 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

- PhD, or Master's degree and 4+ years of quantitative field research experience
- Experience investigating the feasibility of applying scientific principles and concepts to business problems and products
- Experience analyzing both experimental and observational data sets

- Knowledge of R, MATLAB, Python or similar scripting language
- Experience with agile development
- Experience building web based dashboards using common frameworks