Platform Engineer

Remote: 
Full Remote
Contract: 
Work from: 

Offer summary

Qualifications:

Strong knowledge of machine learning principles and best practices., Experience with CI/CD pipelines and automated deployment strategies., Hands-on experience with model lifecycle management, including retraining and drift detection., Expertise in cloud-agnostic ML deployment solutions..

Key responsabilities:

  • Design, build, and manage CI/CD workflows for machine learning models.
  • Develop and implement model lifecycle workflows, including training, deployment, and monitoring.
  • Automate model drift detection and manage re-training cycles to maintain accuracy.
  • Collaborate with data scientists, engineers, and stakeholders to enhance ML infrastructure.

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Job description

Platform Engineer | Remote in Canada
About the Role

We are looking for a Platform Engineer with Machine Learning experience to drive the full lifecycle of machine learning models, from development to deployment and ongoing monitoring. This role requires strong experience in CI/CD workflows, model lifecycle management, and cloud-agnostic solutions. The ideal candidate will work on building and automating ML workflows, ensuring seamless integration and performance of models over time.

Responsibilities
  • Design, build, and manage CI/CD workflows for machine learning models.
  • Develop and implement model lifecycle workflows, including training, deployment, and monitoring.
  • Automate model drift detection and manage re-training cycles to maintain accuracy.
  • Ensure cloud-agnostic deployment strategies and integrate with 3rd-party model lifecycles.
  • Build self-service capabilities to streamline ML model management.
  • Work with trained models, integrate with REST APIs, and oversee model performance monitoring over time.
  • Manage and release artifacts related to machine learning models.
  • Collaborate with data scientists, engineers, and stakeholders to enhance ML infrastructure.
Requirements
  • Strong knowledge of machine learning principles and best practices.
  • Experience with CI/CD pipelines, GitHub Actions, and automated deployment strategies.
  • Hands-on experience with model lifecycle management, including retraining and drift detection.
  • Expertise in cloud-agnostic ML deployment solutions.
  • Familiarity with REST APIs and model serving architectures.
  • Knowledge of monitoring tools for tracking model performance over time.
  • Experience working with third-party models and self-service ML platforms.

This is a great opportunity for an ML Engineer who enjoys building scalable, automated workflows and ensuring machine learning models remain performant and reliable over time.

Required profile

Experience

Industry :
Human Resources, Staffing & Recruiting
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Collaboration

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