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Senior Machine Learning Engineer Jobs in Winnipeg, MB

StandardAero

CF34 Service Engineer

Winnipeg, MB · On-site

... Senior Service Engineer , you'll support the growing volume of CF34 engine work by providing ... Short- & Long-Term Disability * Learning & Training opportunities Raising the Standard of ...

New Flyer

CNC Programming Coordinator

Winnipeg, MB · On-site

Tasks involve optimizing machine performance, ensuring program accuracy and efficiency, and ... On-the-job training in a continuous learning environment (we've invested 10.9 million in 2023)

StandardAero

Analyst, Program & Risk Sr

Winnipeg, MB · On-site

University or college degree in engineering, technologist, finance, or data science with a focus on ... Learning & Training opportunities #LI-LD1 #CES Raising the Standard of Excellence since 1911 With ...

Laivly

Technical Solutions Manager

Winnipeg, MB · Remote

Our solutions help the world's biggest brands leverage artificial intelligence, machine learning ... You'll work directly with customers and across Customer Success, Product, Engineering ...

Wawanesa

Director, Direct Venture Pricing

Winnipeg, MB · On-site

$170 - $220/hr

The role advises senior leaders and balances profitability, member outcomes, regulation, and ... Lead advanced pricing models and methodologies using AI, predictive analytics, machine learning ...

TRUMPF

Field Service Engineer

Winnipeg, MB

CA$35 - CA$45/hr

Whether lasers, machine tools, EUV or electronics - TRUMPF is building technological worlds for ... Do you enjoy travel, learning about new places, and meeting new people? Are you interested in ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Winnipeg, MB

Senior Machine Learning Engineer information

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Winnipeg, MB?

The most popular types of Machine Learning Engineer jobs in Winnipeg, MB are:

What are popular job titles related to Senior Machine Learning Engineer jobs in Winnipeg, MB?

For Senior Machine Learning Engineer jobs in Winnipeg, MB, the most frequently searched job titles are:

Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Winnipeg, MB as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Model Risk & Validation Consultant

Wawanesa Insurance

Winnipeg, MB • Hybrid

CA$120K - CA$145K/yr

Full-time, Part-time

Retirement, PTO

Re-posted 9 days ago

Job description

Job ID: 10224 


Employment Type: New Role

Work Environment: 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; Wawanesa, MB; Vancouver, BC; Calgary, AB; Edmonton, AB; Lethbridge, AB; Toronto (North York), ON; Kitchener, ON; Ottawa, ON; Montreal, QC; Quebec City, QC, Moncton, NB; Dartmouth; NS. 

Working Business Language: English. 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: 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: $120,000 - $145,000. Candidates with salary expectations outside of the range are still encouraged to apply.

About The Wawanesa Mutual Insurance Company
Founded in 1896, The Wawanesa Mutual Insurance Company is one of Canada's largest mutual insurers, 100% owned by its members, with more than $4.1 billion in annual revenue and $12.5 billion in assets. Headquartered in Winnipeg, Wawanesa is the parent company of Wawanesa Life, which provides life insurance solutions throughout Canada, and Western Financial Group, a leading national distributor of personal and business insurance. In March of 2026, Wawanesa entered into an agreement to acquire Everest Insurance Company of Canada to strengthen its commercial insurance capabilities and advance its long-term growth strategy.


Wawanesa proudly serves more than 1.8 million members and we are home to more than 3,000 employees across Canada. The company actively gives back to organizations that strengthen communities, donating more than $4 million annually to charitable organizations, including more than $2 million each year in support of people on the front lines of climate change. Learn more at 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

Reporting into the Enterprise Risk Management function, the Senior Model Risk & Validation Consultant plays a key role in independent review, validation, and challenge of models across the enterprise, including traditional statistical models, actuarial models, machine learning and AI systems.
This role supports the organization's compliance with OSFI Guideline E 23 and evolving regulatory expectations for AI governance, fairness, transparency, and explainability, while promoting strong model risk governance and risk aware decision making across the enterprise. 
The successful candidate will bring strong data science and quantitative modeling expertise, combined with experience in model validation, independent review, or second line oversight, and will work with a high degree of autonomy to challenge model assumptions, methodologies, and controls.

Job Responsibilities

Independent Model Validation & Challenge

  • Conduct independent validation and effective challenge of enterprise wide models across the full model lifecycle, in line with OSFI Guideline E 23.
  • Review model conceptual soundness, data inputs, assumptions, methodology, performance, stability, limitations, and intended use.
  • Assess model risk severity and the adequacy of controls, overlays, monitoring, and governance arrangements.
  • Provide independent validation and risk challenge of AI and ML models, including data quality, bias, explainability and performance monitoring
  • Evaluate model reproducibility, explainability, documentation quality, and transparency.

Model Risk Governance

  • Contribute to the ongoing enhancement of the Model Risk Management Framework, including model inventory management, risk classification, validation standards and documentation requirements.
  • Support Model Risk Adjudication Committee (MRAC) activities by: 
    • Managing and updating enterprise model inventory.
    • Preparing independent validation summaries and risk assessments.
    • Tracking findings, remediation actions, and residual risk acceptance decisions.
    • Provide input into updates to model risk policies, procedures, and guidance, aligned with OSFI and AMF expectations.
    • Promote strong model development and monitoring practices across the organization through guidance, challenge, and education. 
  • Perform other duties as assigned.
Qualifications
  • Bachelor's degree in data science, actuarial science, computer sciences, mathematics, statistics or other related discipline.
  • More than six years of model development or validation experience an asset.
  • Strong programming skills with Python and SQL.
  • Experience validating or reviewing statistical, predictive, machine learning models and AI systems. 
  • Ability to clearly explain complex technical concepts to non technical stakeholders.

#LI-AF1 #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.  
 

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