Amazon-posted 2 days ago
Full-time • Mid Level
Sunnyvale, CA
5,001-10,000 employees

Amazon’s Artificial General Intelligence (AGI) organization is developing a next-generation web search system to support RAG applications across Amazon. Web search is a foundational capability for enabling AGI products across Amazon. We are looking for a Applied Scientist with expertise in information retrieval (IR), content understanding, and natural language processing (NLP) 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 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 As an Applied Scientist, you will apply scientific rigor to your work. You will deliver incrementally, setting up and executing experiments informed by rigorous failure space analysis of prior experiments. You have a knack for writing clear, succinct and informative reports of your experiments. You collaborate and seek guidance from other scientists on your team to define the next experiments. You collaborate closely with engineers to bring your innovations into production. You will continuously with customers and stakeholders to simplify and adapt to deliver for our customers. You will develop state-of-the-art web search technology, including training novel retrieval and ranking models, scaling models and optimizing performance, partnering with engineering to deploy and debug model performance in production, and building and scaling quality training data sets.

  • Apply scientific rigor to your work.
  • Deliver incrementally, setting up and executing experiments informed by rigorous failure space analysis of prior experiments.
  • Write clear, succinct and informative reports of your experiments.
  • Collaborate and seek guidance from other scientists on your team to define the next experiments.
  • Collaborate closely with engineers to bring your innovations into production.
  • Continuously with customers and stakeholders to simplify and adapt to deliver for our customers.
  • Develop state-of-the-art web search technology, including training novel retrieval and ranking models, scaling models and optimizing performance, partnering with engineering to deploy and debug model performance in production, and building and scaling quality training data sets.
  • 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 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 building machine learning models or developing algorithms for business application
  • Experience using Unix/Linux
  • Experience in professional software development
  • PhD in computer science, machine learning, engineering, or related fields
  • 3+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
  • Publications at peer-reviewed conferences (e.g. SIGIR, WWW, CIKM, WSDM, ACL, EMNLP, NAACL, NeurIPS, ICLR)
  • In-depth working knowledge of LLMs
  • Our compensation reflects the cost of labor across several US geographic markets.
  • The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market.
  • Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience.
  • Amazon is a total compensation company.
  • Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
  • For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits .
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