Applied Scientist, AGI Info - Web Information Systems (AI)

TL;DR

Applied Scientist (AI): Developing a next-generation web search system to support RAG applications across Amazon with an accent on information retrieval, content understanding, and natural language processing. Focus on inventing, developing, and deploying novel, scalable algorithms to advance the state-of-the-art in web-scale IR.

Location: Must be based in the US; compensation varies by geographic market. Los Angeles County applicants are considered under specific local ordinances.

Salary: $136,000–$223,400/year

Company

Amazon’s Artificial General Intelligence (AGI) organization is developing foundational AI capabilities for Amazon's products, including a next-generation web search system.

What you will do

• Invent, develop, and deploy novel, scalable algorithms for web-scale Information Retrieval (IR).
• Advance the state-of-the-art in the IR stack and contribute to multi-year research roadmaps.
• Apply scientific rigor to your work, setting up and executing experiments with rigorous failure space analysis.
• Collaborate closely with colleagues and engineers to bring innovations into production.
• Develop state-of-the-art web search technology, including training and optimizing retrieval and ranking models.
• Build and scale quality training data sets.

Requirements

• 3+ years of experience building models for business applications.
• PhD, or Master's degree and 4+ years of CS, CE, ML, or related field experience.
• Experience programming in Java, C++, Python, or a related language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high-performance computing.
• Experience building machine learning models or developing algorithms for business applications.

Nice to have

• Experience using Unix/Linux.
• Experience in professional software development.
• PhD in computer science, machine learning, engineering, or related fields.
• 3+ years of experience building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization, or search.
• Publications at peer-reviewed conferences (e.g., SIGIR, WWW, CIKM, WSDM, ACL, EMNLP, NAACL, NeurIPS, ICLR).
• In-depth working knowledge of LLMs.

Culture & Benefits

• Inclusive culture that empowers Amazonians to deliver the best results for customers.
• Total compensation package includes equity, sign-on payments, and a full range of medical, financial, and other benefits.
• Support for disability accommodations or adjustments during the application and hiring process.