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Software Development Engineer II, AWS SageMaker

Job in Bellevue, King County, Washington, 98009, USA
Listing for: Socket.dev
Full Time position
Listed on 2026-08-22
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, Software Engineer, AI Engineer (Applied/Software), Cloud Engineer - Software
Salary/Wage Range or Industry Benchmark: 144000 - 194000 USD Yearly USD 144000.00 194000.00 YEAR
Job Description & How to Apply Below

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 Sage Maker 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 Amazon Sage Maker Governance team is seeking Software Development Engineer to join our organization. Sage Maker Governance provides the foundational platform capabilities that give enterprise customers trust, visibility, and control over their ML assets se capabilities enable customers to discover, audit, and manage machine learning models and workflows across accounts and organizations through a unified catalog, version-controlled lifecycle management, and end-to-end lineage tracking.

Engineers on the Amazon Sage Maker Governance team are expected to consistently experiment with new technologies and ideas in order to drive innovation and ensure Sage Maker 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 Sage Maker AI

Amazon Sage Maker 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. Sage Maker 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
  • 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.
  • 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.
Basic Qualifications
  • 3+ years of non-internship professional software development experience
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • 1+ years of software development engineer or related occupational experience
  • 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or…
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