Senior Machine Learning Operations Engineer

Job ID: 8167

Working Business Language: This role is considered a head-office role and will be required to communicate with internal stakeholders across Canada where the primary business language utilized is English.

Salary: The salary offered for this role is estimated to be within the following range: $130,000 - $170,000. Candidates with salary expectations outside of the range are still encouraged to apply.

About Us

At Wawanesa, we're proud to 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:

1. Winnipeg, MB
2. Wawanesa, MB
3. Vancouver, BC
4. Calgary, AB
5. Edmonton, AB
6. Lethbridge, AB
7. Toronto, ON
8. Kitchener, ON
9. Thunder Bay, ON
10. Ottawa, ON
11. Montreal, QC
12. Moncton, NB
13. Dartmouth, NS

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 Senior Machine Learning Operations Engineer is responsible for design, development, deployment, and monitoring of machine learning models. The engineer works closely with Data Analysts and 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:

1. Understands and translates business and functional needs into machine learning problem statements.
2. Translates complex machine learning problem statements into specific deliverables and requirements.
3. Assess and improve algorithms, feature sets, and validation metrics received from Data Analysts and ML Engineers to ensure their efficacy for specific problems; modify and retrain models as needed for deployment.
4. 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.
5. Oversee the ongoing enhancement and maintenance of our model agnostic MLOps infrastructure and Python package, ensuring high standards of performance and reliability.
6. Collaborates with development teams to test and deploy machine learning models.
7. Creates metrics to continuously evaluate the performance of machine learning solutions.
8. Ensures adherence to performance standards and compliance to data security and model governance requirements.
9. Keeps abreast with new tools, algorithms, and techniques in machine learning and works to implement them in the organization.

Qualifications

1. More than five years of experience in developing and deploying enterprise-scale machine learning solutions.
2. 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.
3. A strong understanding of probability and statistical models.
4. Proficiency in machine learning algorithms.
5. Ability to run experiments scientifically and analyze results.
6. Experience in code reproducibility and version control.
7. Advanced programming skills with Python and SQL.
8. Proficiency in Linux, Bash, and Docker.
9. Proficiency with AWS ML technology stack or equivalent.
10. Proficiency with CI/CD and Infrastructure as Code.
11. Strong ability to collaborate effectively across multiple teams and stakeholders.
12. Exceptional communication skills and ability to translate technical concepts into appropriate language for all stakeholders.
13. Required to be highly creative and collaborative.
14. Demonstrate good judgment, a sense of urgency.
15. Commitment to high standards of ethics, regulatory compliance, customer service, and business integrity.

Diversity, Equity & Inclusion