Senior Machine Learning DevOps Engineer

Your Job

DarkVision, a Koch Engineered Solutions company, is looking for a Senior Machine Learning DevOps Engineer to join our ML Team.

DarkVision's ultrasound imaging system collects massive, high-resolution datasets.

It is essential that we develop algorithms for automated processing, measuring, classification, and visualization of this data since manual processing is both time-consuming and inconsistent.

Our 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.

You will have the opportunity to apply your skills, experience, and expertise to lead 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.

This position is on-site, with flexible work hours.

Our Team

Based in our state-of-the-art HQ in beautiful North Vancouver, BC, you will work as a core part of the Machine Learning Team and work closely with other Machine Learning DevOps Engineers, Machine Learning Scientists, and Software Engineers.

What You Will Do


* 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.

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.

Who You Are (Basic Qualifications)


* 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...