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Added 3 mins ago
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- $68,000 CAD / year
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- Full-time
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Delta, BC
- $49.2 to $67.08 CAD / hour
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- $23 to $26 CAD / hour
- Full-time
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Closed listing

Realtek Consulting LLC

MLOps Engineer

Toronto, ON, Canada

Contract

This opening has closed.

The original listing is kept below for reference.

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About employer

Job details

Job type: Contract
Closing date: Nov 7, 2026
Posting language: English
Posted: Oct 8, 2026

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Original job description

Archived listing. The details below describe a past opening.

Job Title: Senior AWS SageMaker / MLOps Engineer

Job Location:Toronto,ON-Hybrid (2 days per week in-person at Toronto office preferred)

Long Term Contract

Skills: Digital : Python~Digital : Azure Machine Learning (ML)~Digital: Terraform~AI & Gen AI - Products & Tools

Experience Required: 6-8 Years

Role Description:

We are looking for a highly experienced Senior AWS SageMaker / MLOps Engineer with 8+ years of overall IT experience and strong expertise in building, deploying, and operationalizing Machine Learning solutions on AWS.

The ideal candidate should have hands-on experience with AWS SageMaker, SageMaker Feature Store, MLOps frameworks, and Python development. The resource will be responsible for designing and implementing end-to-end ML pipelines, feature management strategies, model deployment automation, monitoring, and CI/CD integration for enterprise-scale machine learning platforms.

Top 3 Required Skills:

AWS SageMaker (Model Development, Training, Deployment, Monitoring)

AWS SageMaker Feature Store and Feature Engineering

MLOps and Python Development

Top 3 Preferred Skills:

AWS Bedrock / Generative AI

Terraform / CloudFormation

Kubernetes and Docker

Experience Required:

8+ years of overall IT experience

Strong hands-on experience with AWS cloud services

Experience implementing MLOps pipelines and ML lifecycle management

Strong Python development skills

Hands-on experience with SageMaker Pipelines, Model Registry, and Feature Store

Experience with CI/CD tools and cloud-native development practices

Education Requirements:

Bachelor's degree in Computer Science, Engineering, Information Technology, or related field

AWS certifications preferred

About employer

More about this job

Responsibilities

Design and implement end-to-end machine learning pipelines, feature management strategies, and automated model deployment for enterprise-scale platforms. Operationalize machine learning solutions through monitoring, lifecycle management, and CI/CD integration.

Requirements

Requires 8+ years of overall IT experience, strong AWS cloud and Python development skills, and hands-on experience with SageMaker, MLOps pipelines, and machine learning lifecycle management. Experience with SageMaker Pipelines, Model Registry, Feature Store, and cloud-native CI/CD practices is expected; a relevant bachelor's degree is required, and AWS certifications are preferred.

Skills

AWS SageMaker
SageMaker Feature Store
MLOps
Python
Machine Learning
Feature Engineering
SageMaker Pipelines
SageMaker Model Registry
CI/CD
AWS Bedrock
Generative AI
Terraform
CloudFormation
Kubernetes
Docker
Azure Machine Learning

Visa sponsorship

Not detected in the job text

Keywords

AWS
AWS SageMaker
SageMaker Feature Store
SageMaker Pipelines
SageMaker Model Registry
MLOps
Machine Learning
Python
Feature Engineering
Model Development
Model Training
Model Deployment
Model Monitoring
CI/CD
AWS Bedrock
Generative AI
Terraform
CloudFormation
Kubernetes
Docker
Azure Machine Learning
Cloud-Native Development
AWS Certifications
Enterprise Machine Learning Platforms

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