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Azure Cloud Platform Engineer

  • Full Time, onsite
  • eGrove Systems Corporation
  • HybridOntario, United States of America
Salary undisclosed

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Platform ML Engineer

Toronto, Canada (Hybrid) Need local profiles

6+ Months

Skype

Need LinkedIn with Photo, DL and Visa at the time of submission, Need to share this with Client

We are seeking a highly skilled Machine Learning Engineer with hands-on experience in designing and implementing CI/CD pipelines and writing Terraform scripts from the ground up. This role is ideal for someone with a strong engineering mindset and 2+ years of experience working with AI/ML models and systems. You will be responsible for building scalable, automated ML workflows that support the full model lifecycle from training to deployment and ongoing monitoring.
Responsibilities

  • Design and build robust CI/CD pipelines for end-to-end machine learning workflows

  • Write Terraform scripts from scratch to manage infrastructure-as-code in a scalable and cloud-agnostic manner

  • Implement and maintain ML lifecycle workflows, including model training, deployment, performance monitoring, and retraining

  • Automate model drift detection and trigger retraining to maintain model accuracy

  • Create self-service capabilities for internal stakeholders to manage and deploy ML models independently

  • Collaborate with data scientists and DevOps teams to integrate models with REST APIs and third-party services

  • Oversee model release processes, artifact management, and infrastructure provisioning

  • Ensure seamless deployment of models across cloud environments without vendor lock-in

Requirements

  • Minimum 2 years of hands-on experience in AI/ML engineering

  • Proficient in building CI/CD pipelines and infrastructure automation

  • Strong experience writing Terraform scripts from scratch (not templated or assisted)

  • Familiarity with ML Ops practices including model monitoring, retraining, and lifecycle governance

  • Experience with REST APIs and serving models in production environments

  • Knowledge of cloud-agnostic architecture and container orchestration tools

  • Strong collaboration skills and ability to work cross-functionally with engineering and data science teams

Desired Skills and Experience

  • CI/CD

  • TERRAFORM

  • MACHINE LEARNING

  • MACHINE LEARN

  • ML

  • ARTIFICIAL INTELLIGENCE

  • AI

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job

Platform ML Engineer

Toronto, Canada (Hybrid) Need local profiles

6+ Months

Skype

Need LinkedIn with Photo, DL and Visa at the time of submission, Need to share this with Client

We are seeking a highly skilled Machine Learning Engineer with hands-on experience in designing and implementing CI/CD pipelines and writing Terraform scripts from the ground up. This role is ideal for someone with a strong engineering mindset and 2+ years of experience working with AI/ML models and systems. You will be responsible for building scalable, automated ML workflows that support the full model lifecycle from training to deployment and ongoing monitoring.
Responsibilities

  • Design and build robust CI/CD pipelines for end-to-end machine learning workflows

  • Write Terraform scripts from scratch to manage infrastructure-as-code in a scalable and cloud-agnostic manner

  • Implement and maintain ML lifecycle workflows, including model training, deployment, performance monitoring, and retraining

  • Automate model drift detection and trigger retraining to maintain model accuracy

  • Create self-service capabilities for internal stakeholders to manage and deploy ML models independently

  • Collaborate with data scientists and DevOps teams to integrate models with REST APIs and third-party services

  • Oversee model release processes, artifact management, and infrastructure provisioning

  • Ensure seamless deployment of models across cloud environments without vendor lock-in

Requirements

  • Minimum 2 years of hands-on experience in AI/ML engineering

  • Proficient in building CI/CD pipelines and infrastructure automation

  • Strong experience writing Terraform scripts from scratch (not templated or assisted)

  • Familiarity with ML Ops practices including model monitoring, retraining, and lifecycle governance

  • Experience with REST APIs and serving models in production environments

  • Knowledge of cloud-agnostic architecture and container orchestration tools

  • Strong collaboration skills and ability to work cross-functionally with engineering and data science teams

Desired Skills and Experience

  • CI/CD

  • TERRAFORM

  • MACHINE LEARNING

  • MACHINE LEARN

  • ML

  • ARTIFICIAL INTELLIGENCE

  • AI

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job