Amazon Sr Applied Scientist AGI Info 

United States, Washington, Bellevue 

865683405

If you are looking for an opportunity to develop innovative solutions to deep technical problems in web-scale IR, having a massive customer impact, this might be the role for you! As a Sr. Applied Scientist, you will work with smart, passionate colleagues in a fast-paced environment. You will invent, develop, and help deploy novel, scalable algorithms to advance the state-of-the-art in our IR stack. You will keep up with relevant research in the field of IR and publish your work in top-tier conferences. You will develop and help lead the execution of multi-year research roadmaps, enabling the team to focus on the right technical challenges to delight our customers.
Key job responsibilities
You will lead a team of scientists to improve our RAG applications. You will be responsible for: (i) developing novel retrieval and ranking models and partnering closely with engineering to improve model performance; (ii) improve content and query understanding models to deliver improved signal to retrieval and ranking models; (iii) partner closely with content acquisition and client teams to ensure our dependencies are met and we’re delivering value to the end customers, enhancing information grounding for LLMs; (iv) develop science roadmaps for critical web search components; (v) publish your work and remain active in the academic communities; (vi) coach and develop junior scientists.A day in the life

- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience with conducting research in a corporate setting
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.