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Machine Learning Engineer Part Time Jobs in Winnipeg, MB

Canna Cabana

Retail Sales Associate

Winnipeg, MB

Overview Canna Cabana is actively seeking Part-Time Sales Associates who are knowledgeable ... Significant opportunity for growth, experience and learning * Unlimited bonus earning potential ...

New

Canna Cabana

Retail Shift Leader

Winnipeg, MB

Canna Cabana is actively seeking Part-Time Shift Leaders who are knowledgeable, responsible ... Significant opportunity for growth, experience and learning * Unlimited bonus earning potential ...

Canna Cabana

Retail Shift Leader

Winnipeg, MB

Overview Canna Cabana is actively seeking Part-Time Shift Leaders who are knowledgeable ... Significant opportunity for growth, experience and learning * Unlimited bonus earning potential ...

Canna Cabana

Retail Shift Leader

Winnipeg, MB · On-site

Canna Cabana is actively seeking Part-Time Shift Leaders who are knowledgeable, responsible ... Significant opportunity for growth, experience and learning * Unlimited bonus earning potential ...

Canna Cabana

Retail Shift Leader

Winnipeg, MB

Overview Canna Cabana is actively seeking Part-Time Shift Leaders who are knowledgeable ... Significant opportunity for growth, experience and learning * Unlimited bonus earning potential ...

Canna Cabana

Retail Sales Associate

Winnipeg, MB

Canna Cabana is actively seeking Part-Time Sales Associates who are knowledgeable, responsible ... Significant opportunity for growth, experience and learning * Unlimited bonus earning potential ...

New

Wawanesa Insurance

Catastrophe Risk Specialist

Winnipeg, MB · Hybrid

CA$85K - CA$115K/yr

In addition to salary, full-time and part-time permanent employees are eligible for an annual bonus ... Proactively share knowledge in catastrophe-related areas, create learning experiences and foster ...

All JobsMachine Learning Engineer JobsMachine Learning Engineer Part Time JobsMachine Learning Engineer Part Time Jobs in Winnipeg, MB

Machine Learning Engineer Part Time information

What is a machine learning engineer part time?

A Machine Learning Engineer (Part Time) is a professional who designs, builds, and implements machine learning models and algorithms, but works fewer hours than a full-time employee—often on a flexible or project-based schedule. These engineers collaborate with data scientists and software developers to integrate intelligent systems into products or services. Part-time roles are ideal for those seeking work-life balance, students, or professionals supplementing their income. Responsibilities may include data preprocessing, model training, and deployment, but the scope is typically tailored to fit part-time hours.

What are the key skills and qualifications needed to thrive as a machine learning engineer part time?

To thrive as a Machine Learning Engineer Part Time, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and ideally a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, and cloud platforms, as well as experience with version control systems like Git, is typically required. Excellent problem-solving abilities, adaptability, and clear communication are valuable soft skills for collaborating on projects and conveying technical concepts. These skills ensure effective development, deployment, and optimization of machine learning models within the constraints of a part-time role.

How do part-time machine learning engineers typically balance project ownership with limited working hours?

Part-time Machine Learning Engineers often focus on well-defined project segments, collaborating closely with full-time team members to ensure alignment and continuity. Clear communication, thorough documentation, and regular check-ins are key to maintaining progress and integrating their contributions seamlessly. While they may not own entire projects, they often take responsibility for specific modules, models, or experiments, and their schedules are usually coordinated to overlap with team meetings or sprints. This structure allows part-time engineers to add significant value while maintaining a manageable workload.

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

AspectMachine Learning Engineer Part TimeData Scientist Part Time
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with ML frameworksBachelor's or Master's in CS, Statistics, or related; experience with data analysis
Work EnvironmentTech companies, startups, research labs; project-basedBusiness, finance, healthcare; data analysis and reporting
Employer & Industry UsageTech firms, AI startups, R&D departmentsCorporate sectors, consulting firms, research institutions

Machine Learning Engineer Part Time focuses on developing and deploying ML models, while Data Scientist Part Time emphasizes analyzing data to extract insights. Both roles often require similar educational backgrounds and may work in overlapping industries, but their core responsibilities differ. Understanding these distinctions helps job seekers target the right position based on their skills and career goals.

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:

Machine Learning Engineer Part Time jobs near you

Senior Model Risk & Validation Consultant

Wawanesa Insurance

Winnipeg, MB • Hybrid

CA$120K - CA$145K/yr

Full-time, Part-time

Retirement, PTO

Posted 29 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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