Machine Learning Operations Engineer

Date: May 27, 2023

Location: Remote - Canada, CA Quebec, CA Nova Scotia, CA Saskatchewan, CA Manitoba, CA Newfoundland & Labrador, CA Prince Edward Island, CA British Columbia, CA Alberta, CA Ontario, CA

Company: Wawanesa Insurance

Job ID: 6414 

Working Business Language: English


We’re proud to give our employees the flexibility to choose how and where they want to work. In this role, you can decide whether your preference is to work from home (remote), work from the office or a hybrid of time spent at both. You may work from any of the following locations: British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Quebec, New Brunswick, Nova Scotia, Prince Edward Island, Newfoundland & Labrador and/or the Yukon.


The Wawanesa Mutual Insurance Company, founded in 1896, is one of Canada’s largest mutual insurers, with over $4 billion in annual revenue and assets of $12 billion. Wawanesa Mutual, with executive offices in Winnipeg, is the parent company of Wawanesa General, which offers property and casualty insurance in California and Oregon; Wawanesa Life, which provides life insurance products and services throughout Canada; and Western Financial Group, which distributes personal and business insurance across Canada. Wawanesa proudly serves more than two million members in Canada and the United States. Wawanesa actively gives back to organizations that strengthen communities where it operates, donating well above internationally recognized benchmarks for excellence in corporate philanthropy. Learn more at


We are currently looking for dedicated, driven, and enthusiastic individuals who thrive in an environment that welcomes change and are looking for an opportunity for diverse experience and advancement on a growing team.

Job Overview

The Machine Learning Operations Engineer is responsible for development, deployment, and monitoring of machine learning models. The engineer works closely with Data Analysts, ML Engineers in Analytics Exploration and collaborates with Software and Data Engineers to ensure infrastructure and data pipelines are structured to deploy machine learning solutions.    


Job Responsibilities:

  • Understands and translates business and functional needs into machine learning problem statements 
  • Develops scalable solutions that leverage machine learning models to meet enterprise requirements  
  • Works closely with Data Analysts and ML Engineers in Analytics Exploration to develop production grade machine learning models 
  • Support life cycle management of deployed ML models (e.g., retraining, new releases, change management, monitoring and troubleshooting). 
  • Design, build, automate, deploy, monitor, maintain and own machine learning production model and CI/CD pipelines. 
  • Collaborates with development teams to test and deploy machine learning models  
  • Designs and implements metrics to continuously evaluate the performance of machine learning solutions 
  • Maintains and improves the performance of existing machine learning solutions 
  • Keeps abreast with new tools, algorithms and techniques in machine learning and works to implement them in the organization 
  • Performs other duties as assigned. 


  • More than two years of experience in developing and deploying enterprise-scale machine learning solutions. 
  • A minimum of a bachelor's degree in software engineering, data science or computer science or a related quantitative field is required. An advanced degree in a related quantitative field is desired.
  • Strong understanding of probability and statistical models with proficiency in machine learning algorithms.
  • Strong programming skills with Python and SQL are required.
  • Hands-on experience in developing and maintaining APIs (e.g. REST, gRPC, or SOAP) is a must have. 
  • Hands-on experience in specifying infrastructure and infrastructure as a code (e.g.: Docker Swarm, CloudFormation) is a must have. 
  • Hands-on experience with the concepts and capabilities of a cloud data platform and serverless framework is required.
  • Experience in deploying and maintaining reproducible ML models and pipelines.
  • Proficient in developing CI/CD pipelines for both code and ML model development, deploying codes/models to production, monitoring models in production, and managing the model lifecycle in a regulated environment.
  • Familiar with two or more machine learning frameworks (Sklearn, Tensorflow, PyTorch, etc.).
  • Hands-on experience with one or more ML tools like Stagemaker Model Registry, Kubeflow, Metaflow, DVC or MLFlow for lifecycle management or Grafana for monitoring is an asset.
  • Proficiency with AWS MLOps technology stack, particularly Feature Store, Model Registry, Sagemaker, CodeBuild, CodePipeline, Lambda, Cloudformation, ECR and Fargate is an asset.
  • Practical knowledge of ensemble ML models and explainability techniques (e.g. LIME, SHAP or PDPs) is an asset.
  • Ability to effectively communicate technical concepts and results to technical and business audiences in a comprehensive manner.
  • Ability to collaborate effectively across multiple teams and stakeholders, including analytics teams, development teams, and operations.
  • Required to be highly creative and collaborative.
  • Has good judgment, a sense of urgency.
  • Commitment to high standards of ethics, regulatory compliance, customer service and business integrity.

Wawanesa is proud to be one of Manitoba's Top Employers for 2023 recognizing that we are an exceptional place to work! 

Wawanesa provides its employees with a respectful, challenging and rewarding environment where they can maximize their potential while contributing to the company’s goals. Our full-time permanent employees are provided with highly competitive compensation packages (salaries, generous vacation allowance, leave top up, annual bonus plan, premium free benefits and a pension plan). Wawanesa provides a stable environment for its employees in today’s challenging markets. 

Wawanesa is an equal opportunity employer and is committed to fostering a diverse workforce that is equitable and inclusive for all. Wawanesa provides equal employment opportunity to all employees and applicants without regard to an individual’s protected status: race/ethnicity, colour, religion, creed, sex or gender, sexual orientation, gender identity or expression, family or marital status, pregnancy/childbirth or related conditions, national origin, disability, military or veteran status, or any other protected status. Accommodations are available upon request throughout all aspects of the selection process. Candidates requiring accommodations may contact, in confidence,

If you are interested in this exciting, challenging position with Wawanesa, apply today with your Resume.

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