Interested in machine learning, and empowering the world to do more and better machine learning? Amazon SageMaker (https://aws.amazon.com/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 (https://aws.amazon.com/sagemaker/feature-store/). 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.
• Work closely with senior engineers, UX designers, and product managers to develop friendly UI experiences.
• Work closely with engineers to architect and develop the best technical design.
• Develop/maintain operational rigor for the frontend of a fast-growing AWS service.
• Collaborate with other SageMaker SDE's for features that cut across SageMaker.
• Engage with customers and other AWS partners.
• Help with hiring.
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 (https://aws.amazon.com/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.BASIC QUALIFICATIONS
• Bachelor's Degree in Computer Science or related field.
• Equivalent experience to a Bachelor's degree based on 3 years of work experience for every 1 year of education
• 2+ years professional experience in software development.
• Experience with modern programming languages (Java, C#, Python) and open-source technologies.
Experience building tools for data scientists or developers.
• Attuned design sense so can collaborate with UX designers and hold a high bar with "backend" SDE's.
• Experience with with CI/CD in a frontend context.
• Experience establishing and leveraging web analytics.
• Machine learning knowledge and experience.
• Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
• Ability to take a project from scoping requirements through actual launch of the project.
• Experience in communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs.
• Deep hands-on technical expertise in full-stack development.
Software and Programming