Machine Learning Operations Engineer

Job ID: 9646

Employment Type: Existing Role

Working Business Language: English.

Salary: At Wawanesa, salary is only one component of a holistic, comprehensive and competitive offering that we provide to our employees. In addition to salary, full‑time and part‑time permanent employees are eligible for an annual bonus plan, leave of absence top‑up programs and provided with generous vacation time, personal days, premium free benefits and pension plan. The salary offered for this role is determined with consideration to various factors, including but not limited to: your work location, local labour market conditions, external market salary data, internal pay equity and the knowledge, skills, experience and anticipated proficiency in the role. The salary offered is estimated to be within the following range: $110,000 - $140,000. Candidates with salary expectations outside of the range are still encouraged to apply.

About Us
At Wawanesa, we offer a hybrid work environment that offers flexibility to our employees in balancing in‑office (2 days per week OR 15 hours per week in a Wawanesa office) and remote work. You may work from any of the following locations: Winnipeg, MB; Calgary, AB; Toronto (North York), ON.
Wawanesa Mutual Insurance Company (“Wawanesa Mutual”), founded in 1896, is one of Canada’s largest mutual insurers, with over $3.5 billion in annual revenue and assets of $10 billion (CAD). Wawanesa Mutual, with its National Headquarters in Winnipeg, is the parent company of 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 1.7 million members in Canada, and we are home to more than 3,300 employees distributed across the Canadian regions and communities where we operate. We give back to organizations that strengthen communities, donating more than $3.5 million annually to charitable organizations, including over $2 million annually in support of people on the front lines of climate change. We are also proud to be recognized as one of Manitoba’s Top Employers. To learn more visit wawanesa.com.

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.
• Translates complex machine learning problem statements into specific deliverables and requirements.
• Assess and improve algorithms, feature sets, and validation metrics received from Data Analysts and ML Engineers in Analytics Exploration team to ensure their efficacy for specific problems; modify and retrain models as needed for deployment.
• Convert exploration team’s code into robust, production‑level solutions, including CI/CD pipeline integration and infrastructure setup for training and monitoring to meet enterprise requirements.
• Oversee the ongoing enhancement and maintenance of our model agnostic MLOps infrastructure and Python package, ensuring high standards of performance and reliability.
• Collaborates with development teams to test and deploy machine learning models.
• Creates metrics to continuously evaluate the performance of machine learning solutions.
• Ensures adherence to performance standards and compliance to data security and model governance requirements.
• Keeps abreast with new tools, algorithms and techniques in machine learning and works to implement them in the organization.

Qualifications

• More than four years of experience in developing and deploying enterprise‑scale machine learning solutions.
• A bachelor's degree in software engineering, data science or computer science or a related quantitative field [or equivalent work experience] is required. An advanced degree in a related quantitative field is preferred.
• Understanding of probability and statistical models.
• Proficiency in machine learning algorithms.
• Experience in code reproducibility and version control.
• Strong programming skills with Python and SQL.
• Proficiency with Linux, Bash and Docker.
• Proficiency with AWS machine learning technology stack or equivalent.
• Proficiency with CI/CD and Infrastructure as Code.
• 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.
• Previous experience with AWS and Power BI is considered an asset.

#LI-JB3 #LI-Hybrid

Diversity Equity, Inclusion & Belonging

At Wawanesa, we are committed to Diversity, Equity, Inclusion and Belonging (DEIB) and believe that our strength lies in the diversity of our people – this is supported by having a representative workforce.

We welcome applications from all qualified candidates, including racialized persons, women, Indigenous Peoples, persons with disabilities, members of the 2SLGBTQIA+ community, gender‑diverse and neurodiverse individuals, and anyone who can contribute to the further diversification of thought and ideas.

We aim to ensure our recruitment process is accessible to all candidates. If you require accommodations during any stage of the recruitment process, please reach out in confidence to jobs@wawanesa.com.

All Wawanesa job applicants are subject to Wawanesa's Privacy Policy.

Please note that the recruitment process for this position may involve the use of AI tools to screen, assess, or select applicants. All final decisions are taken or reviewed by human recruiters and human hiring leaders in compliance with all applicable legislation.