Publié le mois dernier
AWS Sagemaker / MLOPS Engineer
@ Astra North Infoteck Inc.
Toronto, Ontario
En bref
Astra North Infoteck Inc. is hiring a contract Senior AWS SageMaker / MLOps Engineer in Toronto, ON, on a hybrid arrangement with two days a week in-person preferred. The role builds, deploys and operationalizes machine learning solutions on AWS, requiring 6 to 8 years of experience.
Responsabilités :
- Design and implement end-to-end ML pipelines
- Manage feature engineering with SageMaker Feature Store
- Automate model deployment and monitoring
- Integrate CI/CD for ML platforms
Résumé des exigences :
- 8+ years of overall IT experience
- Hands-on AWS SageMaker experience
- Strong Python and MLOps skills
- Bachelor's degree in a related field
Outils et compétences
Source et dates
Type de source non vérifié · zoho
- Date publiée par l’employeur
- 2026-10-07
- Première détection par notre source
- 2026-10-11
- Mise à jour du dossier source
- 2026-10-11
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Niveau | Senior |
| Domaine | Données et analytique |
| Expérience | 6 an(s) et plus |
| Déplacements | avion : aucun · route : aucun |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
| Formation | Baccalauréat (exigé) |
| Domaines d’études | Computer Science, Engineering, Information Technology |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Astra North Infoteck Inc.
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 426 |
AWS Sagemaker / MLOPS Engineer
Toronto, ON
Hybrid: 2 days per week in-person at Toronto office preferred
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
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