Interested in Machine Learning? As the Frontend Engineering SDE on the SageMaker Neo and SageMaker EdgeManager team, you’ll get to work on bringing seamless UX experience to ML model developers and operators to these two strategic and growing SageMaker services.
The UX work includes working with these technologies:
1. The SageMaker Management Console (https://console.aws.amazon.com/sagemaker )
Expand Console support to develop unique experiences for SageMaker Neo and SageMaker Edge Manager. You work with SageMaker UX designers and and deliver a console experience that enables customers to use the unique features of our services in conjunction with the larger end-to-end ML workflow of SageMaker.
2. Expand SageMaker Studio to develop unique experiences for SageMaker Neo and SageMaker Edge Manager via Studio's AWS ML Notebook authoring and data scientist IDE experience.
From a browser, Studio brings a scalable and collaborative data science workbench and sharable workspace in the cloud to SageMaker customers.
· 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 Neo and Edge Manager features that cut across SageMaker.
· Engage with customers and other AWS partners.
You'll be well supported with by a group with deep technical chops, including multiple senior and principal engineers.
What is SageMaker Neo and Edge Manager?
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 Neo enables ML developers to optimize machine learning (ML) models for inference on SageMaker in the cloud and supported devices at the edge. https://aws.amazon.com/sagemaker/neo/
SageMaker Edge Manager allows ML operators to optimize, secure, monitor, and maintain ML models on fleets of smart cameras, robots, personal computers, and mobile devices.
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
· 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.
Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
· 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.