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Machine Learning Engineer New Grad Jobs in Manitoba

New Flyer

Data Scientist

Winnipeg, MB · On-site

New Flyer is North America's heavy-duty transit bus leader and offers the most advanced product ... Design and develop machine learning models and predictive analytics solutions using data sourced ...

ALS

Geodata Scientist

Winnipeg, MB · Remote

... evaluating and implementing new ML methodologies and workflow improvements. Specific ... Evaluate emerging machine learning, artificial intelligence, and uncertainty quantification ...

New Flyer

CNC Programming Coordinator

Winnipeg, MB · On-site

Develop new and improved methods to maximize program and machine efficiency. * Produces and ... On-the-job training in a continuous learning environment (we've invested 10.9 million in 2023)

Bison Transport

Data Scientist

Winnipeg, MB

The Data Scientist applies advanced mathematical, statistical, and machine learning methods to ... This is an analytical role, not a data engineering or MLOps role; the focus is on formalizing ...

iQmetrix

Senior Data Engineer

Winnipeg, MB · On-site

... workflows, machine learning, and emerging AI use cases. * Build reliable, reusable, and well ... Whether it's on your own or with a team, you aren't afraid to try new things, fail, succeed, and ...

Laivly

Senior Full Stack Software Developer

Winnipeg, MB · On-site +1

Our solutions help the world's biggest brands leverage artificial intelligence, machine learning ... Bring your ideas and try new things * Perform other duties as required As Senior Software Developer ...

New Flyer

Manufacturing Engineer

Winnipeg, MB

On-the-job training in a continuous learning environment (we've invested 10.9 million in 2023 ... Advancement opportunities within our family of companies New Flyer is an equal opportunity employer.

Linamar

Engineer - Controls

Winnipeg, MB

Investigate opportunities and create "Request for Proposal" data packages for new equipment and ... Develop and maintain machinery monitoring and basic reporting in Ignition. * Work with ...

TRUMPF

Field Service Engineer

Winnipeg, MB · On-site

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 ...

Trumpf

Field Service Engineer

Winnipeg, MB · On-site

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 New Grad JobsMachine Learning Engineer New Grad Jobs in Manitoba

Machine Learning Engineer New Grad information

See Manitoba salary details

$26.5K

$109.4K

$202.5K

How much do machine learning engineer new grad jobs pay per year?

As of Jul 19, 2026, the average yearly pay for machine learning engineer new grad in Manitoba is $109,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $150,000.00 per year, depending on experience, location, and employer.

What is a Machine Learning Engineer New Grad job?

A Machine Learning Engineer New Grad job is an entry-level role for recent graduates specializing in machine learning and artificial intelligence. It typically involves developing, training, and deploying machine learning models, working with large datasets, and optimizing algorithms for performance. New grads in this role often collaborate with data scientists, software engineers, and product teams to integrate models into applications. Employers look for proficiency in programming (Python, TensorFlow, PyTorch), a strong foundation in ML concepts, and experience with data processing. This role provides an opportunity to gain hands-on industry experience and grow technical skills in real-world applications.

What are the key skills and qualifications needed to thrive in the Machine Learning Engineer New Grad position, and why are they important?

To thrive as a Machine Learning Engineer New Grad, a strong background in computer science, statistics, and mathematics, often supported by a relevant degree, is essential. Familiarity with programming languages like Python or Java, machine learning frameworks (such as TensorFlow or PyTorch), and basic knowledge of data tools and cloud platforms is typically required. Effective problem-solving, eagerness to learn, and clear communication help new grads excel when collaborating on projects and learning from senior team members. These skills and qualities are vital for adapting quickly, contributing to team goals, and building a successful foundation in this fast-evolving technical field.

What are the typical day-to-day tasks of a Machine Learning Engineer New Grad?

As a Machine Learning Engineer New Grad, your daily tasks often include collecting and preprocessing data, developing and testing machine learning models, and analyzing model performance. You may work closely with data scientists and software engineers to integrate models into production systems and address real-world business problems. Participating in team meetings, code reviews, and collaborative projects is common, providing opportunities to learn best practices and receive mentorship. This hands-on, varied workload helps you quickly build technical and collaborative skills early in your career.

What cities in Manitoba are hiring for Machine Learning Engineer New Grad jobs? Cities in Manitoba with the most Machine Learning Engineer New Grad job openings:
Machine Learning Engineer New Grad jobs near you
Infographic showing various Machine Learning Engineer New Grad job openings in Manitoba as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 78% Physical, 4% Hybrid, and 18% Remote job distribution, with an average salary of $109,405 per year, or $52.6 per hour.
Manager, Machine Learning Operations (MLOps)

Manager, Machine Learning Operations (MLOps)

Wawanesa Insurance

Winnipeg, MB • Hybrid

CA$140K - CA$180K/yr

Other

Retirement, PTO

Re-posted 29 days ago

Job description

Job ID: 9789 


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: $140,000 - $180,000.  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.
 

The 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 Manager, Machine Learning Operations (MLOps) contributes to Wawanesa's success by bringing your passion for predictive modeling and machine learning. In this role, you will lead the Machine Learning Operations (MLOps) function, ensuring scalable, reliable, and cost-effective deployment of machine learning solutions across the enterprise. The manager is leading a team responsible for taking machine learning applications to support decision making across the organization from concept to production, with accountability for platform architecture, production reliability, governance, and lifecycle management.   

Job Responsibilties

  • Work directly with organizational leaders to introduce advanced analytics to all functions within the organization, and to foster the advancement and adoption of analytic assets.
  • Develop and advance analytic standards and processes that enable all aspects of advanced analytics including applied research, proof of concept, deployment of production grade ethical machine learning models, model monitoring and measurement.
  • Own and evolve the enterprise MLOps platform strategy, including CI/CD for ML, model registry, feature management, orchestration, monitoring, and observability frameworks.
  • Establish standardized deployment patterns and infrastructure-as-code practices to reduce bespoke solutions and increase reuse across teams.
  • Model lifecycle governance from development through validation, deployment, monitoring, retraining, and retirement.
  • Identify and organize educational initiatives aimed at the development of overall inter- and intra-departmental knowledge.
  • Keeps abreast with new tools, algorithms and techniques in machine learning and works to implement them in the organization.
  • Perform other duties as assigned.
Qualifications
  • A minimum of five years of experience in developing and deploying enterprise-scale machine learning solutions, and one year of people leadership with proven ability to build high performing teams.
  • Strong business acumen with advanced analytical and problem-solving skills, with the ability to recognize, and identify critical issues.
  • Excellent interpersonal, presentation and communication skills, with the ability to effectively convey complex ideas in a simple, persuasive, and eloquent manner.
  • Comfortable confronting difficult issues and diplomatic in delivery of challenging messages.
  • Ability to establish and maintain good relationships with key stakeholders.
  • Advanced planning and organizing skills, with the ability to manage and prioritize a busy workload and multiple projects.
  • Knowledge and experience in the insurance industry is considered an asset.

#Li-Hybrid #LI-JB3


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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