DESCRIPTION

Amazon Transportation Services is seeking a talented Applied Scientist in the field of Large Language Models, AI, and Natural Language Processing, to invent and build scalable solutions that will transform how one of the world’s largest transportation networks operate.
In this role, you will tackle complex challenges in Natural Language Processing and Information Retrieval, working at the intersection of advanced AI research and practical business applications. Working alongside fellow scientists, engineers, and product leaders, you will develop context-aware AI solutions that streamline our transportation operations. The person in this role will have a deep interest in applied AI research and experience building practical, large-scale machine learning systems.

Key job responsibilities

• Design and implement advanced AI systems that leverage deep learning and natural language processing at enterprise scale
• Create intelligent agent frameworks that combine LLMs with structured and unstructured data sources to drive automated insights
• Lead technical evaluation of model performance, establishing metrics for accuracy, latency, and business impact
• Build production-ready AI solutions that integrate with Amazon’s existing systems and operational workflows
• Establish frameworks for continuous model improvement through automated feedback loops and performance monitoring
• Partner with engineering teams to design scalable architectures supporting real-time AI capabilities across multiple use cases
• Collaborate with stakeholders across science, product, and operations teams to deliver high-impact AI solutions

BASIC QUALIFICATIONS

• 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 in patents or publications at top-tier peer-reviewed conferences or journals
• Experience programming in Java, C++, Python or related language
• Strong foundation in Machine Learning, NLP, and Information Retrieval

PREFERRED QUALIFICATIONS

• Experience in investigating, designing, prototyping, and delivering new and innovative system solutions
• Demonstrated expertise in: LLM-powered agent development and orchestration, RAG implementations, particularly GraphRAG, and AWS AI Services (Bedrock, SageMaker)
  Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
  Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
  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. This position will remain posted until filled. Applicants should apply via our internal or external career site

• Design and implement advanced AI systems that leverage deep learning and natural language processing at enterprise scale
• Create intelligent agent frameworks that combine LLMs with structured and unstructured data sources to drive automated insights
• Lead technical evaluation of model performance, establishing metrics for accuracy, latency, and business impact
• Build production-ready AI solutions that integrate with Amazon’s existing systems and operational workflows
• Establish frameworks for continuous model improvement through automated feedback loops and performance monitoring
• Partner with engineering teams to design scalable architectures supporting real-time AI capabilities across multiple use cases
• Collaborate with stakeholders across science, product, and operations teams to deliver high-impact AI solution