SDE II: AI Model Orchestration & Large-Scale Training

Amazon; Bellevue (WA); On-site; USD 144,000 - 194,000; Full time

Benefits offered by this job

RSUs

Health insurance

401(k) matching

Job summary

Amazon is seeking a Software Development Engineer II for the AWS SageMaker AI team in Bellevue, WA. You will design, build, and operate distributed systems at the core of Model Factory, enabling scalable training, customization, and evaluation of foundation models.

You will own components end-to-end, collaborating with ML scientists and platform teams to deliver reliable, self-service capabilities, and mentor junior engineers.

Qualifications

• 3+ years of non-internship professional software development experience.
• 2+ years of non-internship design or architecture experience for large-scale systems.
• 1+ years of software development engineer or related experience.
• 1+ years of designing and developing large-scale distributed software applications.

Responsibilities

• Design, build, test, and operate services that orchestrate foundation-model data preparation, training, evaluation, and deployment as reliable, contract-validated workflows.
• Own delivery of individual components end-to-end from design to deployment and on-call operations.
• Build and extend compute-backend integrations and job launchers for large-scale training jobs across SageMaker, EMR, AWS Batch, and Kubernetes/EKS.
• Improve resiliency and operability for long-running distributed jobs with checkpointing, fault detection, retries, and observability.
• Contribute to the SDK, workflow orchestration, and schema/contract layers used to declare and run jobs, and to CDK infrastructure.

Skills

C++

Java

C#

Object Oriented Design

Distributed systems

Education

Bachelor's degree in Computer Science/Engineering/Mathematics

Tools

Airflow

Step Functions

Kubernetes/EKS

AWS CDK/CloudFormation

Job description

Amazon is seeking a Software Development Engineer II for the AWS SageMaker AI team in Bellevue, WA. You will design, build, and operate distributed systems at the core of Model Factory, enabling scalable training, customization, and evaluation of foundation models.

You will own components end-to-end, collaborating with ML scientists and platform teams to deliver reliable, self-service capabilities, and mentor junior engineers.