Machine Learning Engineer II, Intl. Seller Growth Specialist

1 week ago


Seattle, Washington, United States Amazon Full time
About the Role

We are seeking a highly skilled Machine Learning Engineer II to join our International Seller Growth team at Amazon. As a key member of our team, you will be responsible for designing, implementing, and operating large-scale, high-volume, high-performance data structures for analytics and data science.

Key Responsibilities:

  • Design and Implement Data Structures: Develop and deploy models and pipelines that scale, and gather business and functional requirements to translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
  • Collaborate with Cross-Functional Teams: Work closely with Applied Scientists, Data Scientists, and Data Engineers to help adopt best practices in ML system creation, experimentation setup, and documentation.
  • Identify Opportunities for Improvement: Identify opportunities in existing data/ML solutions for improvements and develop reusable cloud infrastructure and deployment patterns to accelerate productionalization.

Example Projects:

  • Setting up a Dev environment for experimenting multiple embedding models for RAG setup
  • Implementing a robust experimentation platform to test, iterate, and optimize the Conversation Assistants' performance across key RAG metrics
  • Developing reusable cloud infrastructure and deployment patterns to accelerate productionalization
  • Integrating disparate ML solutions into cohesive customer experiences

Requirements:

  • Experience with machine learning techniques such as pre-processing data, training and evaluation of classification and regression models, and statistical evaluation of experimental data.
  • 2+ years of non-internship professional ML-software development experience
  • Programming experience with at least one modern language such as Python, Java, C++, or C# including object-oriented design
  • 2+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
  • Experience in building production quality and large scale deployment of applications related to NLP and ML

Preferred Qualifications:

  • Advanced knowledge of performance, scalability, enterprise system architecture, and engineering best practices
  • Academic and/or industry experience with one of more of the following domains: computer vision, deep learning, machine learning or large-scale distributed systems.


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