DevOps Engineer

3 weeks ago

Vancouver, Canada Insight Global Full time

Insight Global is seeking an MLOps Engineer for one of our innovative technology clients based out of Vancouver BC. Their ultrasound imaging application requires a scalable and robust infrastructure that can accommodate the custom deep learning models we are developing, and the amount of data involved. The role will involve leading the design and development of a cutting-edge workflow architecture that will enable the development, training, and automated deployment of ML models developed by our dedicated team of ML Scientists.

  • Guide, build, and manage the development of pipelines for ML systems in production.
  • Lead the design and deployment of Cloud infrastructure in AWS in accordance with MLOps industry best practices.
  • Coordinate cross-team efforts for feature/requirement creation; determine the best way to train, build, deploy, and monitor production models.
  • Understand the big picture; determine the best way to collect and train data, and ensure continuous improvement and development; assign the work to individuals.
  • Actively maintain collaboration and knowledge sharing with other teams.



Must Haves:

  • 5+ years of professional experience in a DevOps role
  • Bachelor's degree in Computer Science, Software Engineering, or a STEM discipline with a focus on software engineering or equivalent experience
  • Hands-on experience with designing, developing, and maintaining a data warehouse.
  • Experience with pipeline tools such as Kubeflow, Prefect, or AWS SageMaker.
  • Experience with deployment and orchestration tools including Docker and Kubernetes
  • Experience with model, data, and experiment versioning, monitoring, and tracking.
  • Experience building and managing CI/CD pipelines
  • Experience with data workflow and container orchestration tool
  • Expert AWS knowledge
  • Experience in architect or technical lead

Plusses:

  • Experience deploying computer vision deep learning algorithms.
  • Experience creating machine learning algorithm
  • Professional experience in building, operating, orchestrating, and maintaining cloud infrastructures for ML systems in production.
  • Masters or PhD

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