Sr. Applied Scientist, AGI Info

Amazon•Bellevue, WA

11d

About The Position

Amazon’s Artificial General Intelligence (AGI) organization is developing a next-generation web-scale information retrieval system to support RAG applications across Amazon. We are looking for a Sr. Applied Scientist with expertise in information retrieval (IR) and ranking to join the team! 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 A mix of (i) technical deep dives: working with the team to develop the right models, setup good experiments, debug models, etc. (ii) coaching and development: providing feedback, setting up mechanisms to ensure the team’s success, and (iii) working with customers and dependency teams to ensure delivery.

Requirements

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.

Responsibilities

Lead a team of scientists to improve our RAG applications.
Developing novel retrieval and ranking models and partnering closely with engineering to improve model performance
Improve content and query understanding models to deliver improved signal to retrieval and ranking models
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
Develop science roadmaps for critical web search components
Publish your work and remain active in the academic communities
Coach and develop junior scientists

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