Be a part of the rapid growth of AWS SageMaker! Since it launch in Nov 2017, AWS ML platform SageMaker has seen unprecedented customer adoption. SageMaker helps engineers and data scientists build, train and deploy ML models at scale. Built-in algorithms (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
) have fueled this growth and provided customers with state-of-the-art, highly optimized algorithms for a few common ML problems. As an engineer in the AWS-ML platform team, you'll build world-class machine-learning algorithms that make data science faster and simpler on the SageMaker platform.
Delivering reliable, scalable, and high-performance algorithms for SageMaker requires engineers with exceptional technical expertise to work closely with exceptional ML, CV and NLP scientists. You will be working with terabytes of text, images, and other types of data to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. 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.