Remote Aws Machine Learning Jobs in Everett, WA (NOW HIRING)

Are you a highly skilled and innovative SDE with a passion for developing new machine learning capabilities and driving innovation to build customer-centric solutions in Amazon SageMaker AI. Are you interested to play a key role in developing software applications at AWS. We invite you to join us and be part of making history.
The Data Preparation team enables customers to generate high-quality synthetic data and ensure data quality across AI workflows

The goal is that every AI practitioner on SageMaker can produce tailored, high-quality datasets for model training, fine-tuning, and evaluation without needing deep data engineering expertise.
As a Senior SDE on this team, you will own the design and delivery of large-scale, highly available distributed systems that power the end-to-end ML development experience. You will drive technical vision, influence product direction, and raise the engineering bar across the organization.

You will be responsible for leading the team in building and maintaining capabilities within our best-in-class machine learning offering, as well as scaling those systems to support our customers' workflow orchestration automation needs.
Engineers on the Amazon SageMaker Data Preparation team are expected to consistently experiment with new technologies and ideas in order to drive innovation and ensure SageMaker remains a best-in-class service. You will be held to the highest standards of engineering and operational excellence, including building highly resilient and scalable systems, producing clear and effective technical documentation, actively contributing to discussions on strategic direction, and continuously raising the bar. Most importantly, you will have the opportunity to collaborate with a team of highly skilled and dedicated engineers who share a commitment to achieving new levels of success.
About Amazon SageMaker AI
Amazon SageMaker AI is a fully managed machine learning service that simplifies the process of building, training, and deploying machine learning models

It abstracts away the undifferentiated heavy-lifting associated with large-scale machine learning implementations, allowing developers and data scientists to focus on the core modeling and problem-solving aspects of their work. SageMaker is currently utilized by businesses of all sizes, including some of the world's leading enterprises, across a growing number of geographic regions.
About the team
Why AWS.
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform

We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

Key job responsibilities
**Technical Leadership** - Lead the architecture, design, and implementation of complex software systems. Define long-term technical strategy and drive alignment across teams.
**System Design & Delivery** - Own end-to-end delivery of large-scale distributed services with high availability, low latency, and operational excellence.
**Cross-Team Influence** - Collaborate with product, science, and partner engineering teams to define roadmaps and deliver customer-obsessed solutions.
**Mentorship & Bar Raising** - Mentor engineers across levels, conduct design and code reviews, and actively raise the technical and operational bar for the team.
**Operational Excellence** - Champion best practices in CI/CD, observability, testing, and incident management. Drive a culture of ownership and accountability.
**Innovation** - Identify opportunities to simplify, automate, and improve the developer experience

Contribute to patents, publications, or open-source projects where appropriate.
**Customer Obsession** - Deeply understand customer workflows and pain points; translate insights into scalable, intuitive platform capabilities.