Machine Learning Operations 3 - 8 Yrs

Requirements

Job Summary

We are looking for an experienced MLOps Practitioner to join our Canada Post project. The ideal candidate should have strong hands-on experience in machine learning operations, model lifecycle management, and AWS-based ML platforms.

Key Responsibilities

• Design and implement MLOps processes for machine learning model development and deployment.
  
• Work on model training, evaluation, retraining, and monitoring.
  
• Perform feature engineering and support end-to-end ML workflows.
  
• Work with core Machine Learning frameworks and tools.
  
• Build and maintain scalable ML pipelines and model lifecycle processes.
  
• Utilize AWS SageMaker Unified Studio for ML development and operational workflows.
  
• Monitor model performance and implement model retraining strategies when required.
  

Required Skills

• Strong hands-on experience in MLOps.
  
• Experience with:
  • Model Training & Evaluation
    
  • Feature Engineering
    
  • Model Retraining
    
  • Model Monitoring
    
  • Core ML Frameworks
    
• Strong experience with AWS SageMaker Unified Studio.
  

Good to Have

• Experience with Terraform.
  
• Strong understanding of AWS Infrastructure.
  
• Experience with AWS services related to ML/AI workloads.
  
• Knowledge of cloud-based MLOps architecture and best practices.
  

Candidate Profile

• Strong MLOps hands-on experience with an understanding of the complete ML lifecycle.
  
• Ability to work independently in a project environment.
  
• Strong troubleshooting and problem-solving skills.
  
• L35-level candidates are preferred.
  

Interested candidates can apply with their updated resume mentioning relevant MLOps and AWS SageMaker experience.

Benefits