Senior Machine Learning DevOps Engineer

2 months ago

Vancouver, British Columbia, Canada DarkVision Full time
About the Role

DarkVision, a Koch Engineered Solutions company, is seeking a Senior Machine Learning DevOps Engineer to join our Machine Learning Team. Our ultrasound imaging system collects massive, high-resolution datasets, requiring the development of algorithms for automated processing, measuring, classification, and visualization of this data.

Key Responsibilities
  • Design and develop pipelines for ML systems in production, ensuring scalability and robustness.
  • Lead the design and deployment of Cloud infrastructure in AWS, adhering to MLOps industry best practices.
  • Coordinate cross-team efforts for feature/requirement creation, determining the best way to train, build, deploy, and monitor production models.
  • Understand the big picture, determining the best way to collect and train data, and ensure continuous improvement and development.
  • Maintain collaboration and knowledge sharing with other teams.
Opportunities to Learn and Work On
  • Develop state-of-the-art computer vision deep learning technologies.
  • Introduce new frameworks, tools, and processes.
  • Build ML production systems for novel applications.
  • Independence to carry out self-guided research projects and POCs.
Requirements
  • Professional experience in building, operating, orchestrating, and maintaining cloud infrastructures for ML systems in production.
  • Experience building and managing CI/CD pipelines for ML systems in production.
  • Experience with data workflow and container orchestration tools.
  • Familiar with one or more machine learning frameworks.
What Will Put You Ahead
  • 3+ years of professional experience in a similar role and using AWS services and PyTorch.
  • Bachelor's degree in Computer Science, Software Engineering, or a STEM discipline with a focus on software engineering or equivalent experience. Master's degree will be considered a plus.
  • 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 such as Terraform, Docker, or Kubernetes.
  • Experience with model, data, and experiment versioning, monitoring, and tracking.
  • Experience deploying computer vision deep learning algorithms.
  • Excellent communication skills with a proven record of leading cross-discipline projects.
Benefits

This role is eligible for a competitive salary range of $130,000 to $190,000 per year, variable pay, and a full benefits package. The role is also eligible for flexible hours and work environment, and access to our state-of-the-art facilities.

We seek to enable the best work environment that helps you and the business work together to produce superior results.

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