Amazon Selection and Catalog Systems (ASCS) is looking to leverage Large Language Models (LLM) and Generative AI to solve complex challenges related to the completeness, consistency, and correctness of Amazon's product data, which powers the online buying experience for customers worldwide. The sheer scale (billions of products), diversity, and multitude of input sources make this a challenging problem.
Requirements
- 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 with popular deep learning frameworks such as MxNet and Tensor Flow
- Experience with Large Language Model (LLM) and Foundational Model fine-tuning, or reinforcement learning techniques
Responsibilities
- Design and implement LLM-based solutions to improve catalog data quality and completeness
- Conduct experiments and A/B tests to validate model improvements and measure business impact
- Optimize large language models for quality and cost on catalog-specific tasks
- Collaborate with engineering teams to deploy models at scale serving billions of products
Other
- 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
- Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
- 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.
- Our compensation reflects the cost of labor across several US geographic markets.
