Machine Learning Engineer II, Intl. Seller Growth

$129,300 - $223,600/Yr

Amazon - Seattle, WA

Full-time - Mid Level

Seattle, WA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Machine Learning Engineer II position within the International Seller Services (ISS) Central Analytics Data Engineering team focuses on developing and maintaining advanced data and machine learning infrastructure. The role involves collaborating with various teams to create scalable, efficient, and secure analytical solutions that leverage machine learning and AI technologies to enhance customer experiences.

Responsibilities

• Design, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.
• Develop and deploy models and pipelines that scale.
• Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
• Collaborate with Applied Scientists, Data Scientists, and Data Engineers to help adopt best practices in ML system creation, experimentation setup, and documentation.
• Identify opportunities in existing data/ML solutions for improvements.

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 of new and current systems.

Nice-to-haves

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

Benefits

• Full range of medical benefits
• Financial benefits including equity and sign-on payments
• Diversity and inclusion programs