Interested in machine learning, and empowering the world to do more and better machine learning? Amazon SageMaker (), Amazon Web Service's (AWS) fully managed Machine Learning (ML) platform team is building customer-facing services to catalyze data scientists and developers in their machine learning endeavors.
SageMaker takes away the heavy-lifting normally associated with large-scale Machine Learning implementations, so that developers and scientists can focus on solving the business problem at hand.
We are looking for a full-stack / frontend engineer who excels at working in an agile environment, takes pride in tackling the hardest challenges, and is excited about our mission to democratize machine learning.
You will work in a diverse team to build and evolve the next-generation of ML data and feature management services (). As a Frontend Engineer, you will design, implement, test, operate, and evolve the UI components for this new product.
Your work will enable customers to build and run end-to-end ML feature management services.
Key Responsibilities :
You'll be well supported with by a group with deep technical chops, including multiple senior and principal engineers.
At SageMaker, there are immense learning as well as growth opportunities. This is a great team to come to have a huge impact on AWS and the world's customers we serve!
What is SageMaker?
Amazon SageMaker () is a fully-managed Machine Learning platform that makes it easy to build ML models, manage them, and integrate them with custom applications for batch or online predictions.
SageMaker takes away the heavy-lifting normally associated with large-scale Machine Learning implementations so that developers and scientists can focus on the truly creative work of modeling and solving the business problem at hand.
Experience building tools for data scientists or developers.