Platform Engineer

Role-Platform Engineer
Location: Toronto, ON (Hybrid)
Duration- Contract

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.