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Senior Machine Learning Engineer, SageMaker Inference

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Are you interested in helping AWS customers by building ML-distributed systems to deploy Generative AI models for inferencing at scale? SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. Specifically, the SageMaker Inference Platform enables customers to deploy ML models at scale to run high throughput, low-latency CPU/GPU/Inferentia workloads and monitor the quality of the models and data in production. The team is currently focused on solving core infrastructure problems for Generative AI inference serving needs of both internal and external customers. We're moving fast, and this is a great team to join and make a huge impact on AWS especially in the Generative AI space. To learn more about the product, please visit https://docs.aws.amazon.com/sagemaker/latest/dg/deploy-model.html

Key job responsibilities

A day in the life

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 conferences.

About the team

SageMaker Inference team is innovating and modernizing the inference experience that enables the customers to customize their inference workloads. This is an opportunity to establish technical vision, shape product strategy, and build within a proven, high-growth service.

Internal job description

We own AWS SageMaker (https://w.amazon.com/index.php/AWS/AmazonAI/Platform/IronMan) to empower the world to do more and better Machine Learning.

This is recent launch from team made GA in Q2 2026 (https://docs.aws.amazon.com/sagemaker/latest/dg/realtime-endpoints-heterogeneous.html)

We are looking for internal candidates with prior experience building large scale systems, who are excited about getting into the ML domain.

Basic qualifications

Preferred qualifications

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

USA, WA, Bellevue - 168,100.00 - 227,400.00 USD annually

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