Interested in Machine Learning, and empowering the world to do more and better machine Learning? With Amazon SageMaker, Amazon Web Service’s (AWS) Machine Learning platform team is building customer-facing services to catalyze data scientists and software engineers in their machine learning endeavors. This product is a blend of HTTP API’s, low and high-level SDK’s, and an AWS Console UI.

You will design, implement, test, document, and support cross-cutting services to help customers do machine learning at scale. You’ll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will serve as a key technical resource in the full development cycle, from conception to delivery and maintenance. You will produce comprehensive, usable software documentation; recommend changes in development, maintenance and system standards. You will own delivery of entire piece of the system and serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers.
We’re moving fast, and this is a great team to come to to have a huge impact on AWS and the world’s customers we serve!
Job Code : 10016

Key job responsibilities
- Act as tech lead for gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture.
- Engage with customers and other AWS partners
- Serve as technical lead on complex projects using best practice engineering standards, and hire/mentor junior development engineers
- You’ll be well supported with by a group with deep technical chops, including multiple senior and principal engineers.
- Lead teams of engineers to deliver results in multiple layers of the stack in some of the most challenging problem spaces in the industry.