Senior Machine Learning DevOps Engineer

4 weeks 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, and we need someone to develop algorithms for automated processing, measuring, classification, and visualization of this data.

Key Responsibilities

  • Guide 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.
  • Actively maintain collaboration and knowledge sharing with other teams.

Opportunities to Learn and Work On

  • The development of state-of-the-art computer vision deep learning technologies.
  • Introduction of new frameworks, tools, and processes.
  • Building 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.

General Salary Range

For this role, we anticipate paying $130,000 to $190,000 per year. This role is eligible for variable pay, issued as a monetary bonus or in another form. This role is also eligible for the full benefits package, flexible hours and work environment, and access to our state-of-the-art facilities.

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