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Senior AWS SageMaker / MLOps Engineer

  • Toronto, ON, Canada

Contract

This opening has closed.

The original listing is kept below for reference.

Job details

Job type
Contract
Closing date
Experience
8+ years of overall IT experience.
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

8+ years of overall IT experience.

Strong hands-on experience with AWS SageMaker (training, deployment, monitoring, and inference).

Experience with SageMaker Pipelines, Model Registry, and Feature Store.

Strong expertise in MLOps concepts and ML lifecycle management.

Proficiency in Python programming.

Experience with AWS cloud services and cloud-native application development.

Experience with CI/CD tools such as Jenkins, GitHub Actions, or AWS CodePipeline.

More about this job

Responsibilities

Build and manage machine learning workflows using AWS SageMaker, including model training, deployment, monitoring, and inference. Support MLOps and machine learning lifecycle management using SageMaker Pipelines, Model Registry, and Feature Store.

Requirements

Requires 8 or more years of overall IT experience and strong hands-on experience with AWS SageMaker and MLOps. Candidates should be proficient in Python and experienced with AWS cloud services, cloud-native application development, and CI/CD tools such as Jenkins, GitHub Actions, or AWS CodePipeline.

Skills

  • AWS SageMaker
  • MLOps
  • Python
  • AWS Cloud Services
  • SageMaker Pipelines
  • SageMaker Model Registry
  • SageMaker Feature Store
  • CI/CD
  • Jenkins
  • GitHub Actions
  • AWS CodePipeline
  • Cloud-Native Application Development
  • Model Training
  • Model Deployment
  • Model Monitoring

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Data & Analytics
  • Consulting

Keywords

  • AWS SageMaker
  • MLOps
  • Python
  • AWS Cloud Services
  • SageMaker Pipelines
  • Model Registry
  • Feature Store
  • CI/CD
  • Jenkins
  • GitHub Actions
  • AWS CodePipeline
  • Cloud-Native Application Development
  • Model Training
  • Model Deployment
  • Model Monitoring
  • Inference
  • IT Services
  • IT Consulting

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