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Entry Level Machine Learning Engineer Jobs in Toronto, ON

Td

Research Machine Learning Scientist

Toronto, ON

CA$140K - CA$250K/yr

Collaborate closely with our engineering team in a fast-paced startup environment and see your ... Proven track record of applying machine learning to solve real-world problems ...

Waabi

Research Engineer

Toronto, ON · On-site +1

CA$122K - CA$215K/yr

Qualifications: - Bachelor's in computer science, engineering, machine learning, or a related technical discipline. - Experience working on applied research projects. - Passion for taking research ...

Apertera

Generative AI Engineer

Toronto, ON · On-site

Work closely with machine learning engineers and data engineers to design, build, and test models. * Develop efficient and scalable algorithms for training and inference of generative models ...

Td

Applied Machine Learning Scientist I

Toronto, ON · On-site +1

CA$105K - CA$125K/yr

About the Role We are looking for a highly motivated Applied Machine Learning Scientist to join the ... Experience with structured and unstructured data, feature engineering, and model interpretability ...

THOMSON REUTERS

Lead Research Engineer

Toronto, ON · On-site +1

We hire engineers and specialists across a variety of AI research areas to drive the company ... Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ...

THOMSON REUTERS

Research Engineer

Toronto, ON · Hybrid

Ability to understand, apply,integrateand deploy Machine Learning capabilities and techniques into other systems. * Familiarity with the Python data science stack through exposure to libraries such ...

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All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in Toronto, ON

Entry Level Machine Learning Engineer information

See Toronto, ON salary details

$20K

$83.2K

$177.5K

How much do entry level machine learning engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for entry level machine learning engineer in Toronto, ON is $83,214.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,990.00 and $94,002.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the most commonly searched types of Machine Learning Engineer jobs in Toronto, ON? The most popular types of Machine Learning Engineer jobs in Toronto, ON are:
What are popular job titles related to Entry Level Machine Learning Engineer jobs in Toronto, ON? For Entry Level Machine Learning Engineer jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Toronto, ON look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Toronto, ON are:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 16% Internship, and 84% Full Time. Highlights an 72% In-person, 14% Hybrid, and 14% Remote job distribution, with an average salary of $83,214 per year, or $40 per hour.

Machine Learning Software Engineer

Royal Bank of Canada

Toronto, ON • On-site

Full-time

Re-posted 3 days ago

Job description

Job Description


What's the opportunity?

RBC Borealis is looking for an enthusiastic software developer who's excited by the opportunity of working on challenging problems at the intersection of machine learning and the financial services industry. As a Machine Learning Software Engineer, you'll be responsible for owning and delivering a project end to end - everything from data pre-processing and exploration, to building and scaling ML algorithms and pipelines, to deployment and monitoring of production systems. At RBC Borealis, you'll be joining a team that works directly with leading researchers in machine learning, has access to rich and massive datasets, and offers the computational resources to support cutting-edge machine learning R&D.

Your responsibilities include:

  • To build cutting edge ML solutions throughout the research and product development lifecycle;

  • To play a key role in the design and development of Borealis' machine learning products;

  • To partner with RBC Borealis's research and product teams to ensure the seamless delivery of these products;

  • To apply engineering and data best practices to build robust and scalable large-scale machine learning software systems;

  • To support projects with thorough documentation, design decisions, and technical advisory.

You're our ideal candidate if you have:

  • Experience building modular and robust software systems in Python or similar language;

  • Knowledge of professional software engineering best practices for the full software development life cycle, including testing methods, coding standards, code reviews and source control management;

  • Experience working across the entire ML research and product lifecycle from prototyping to production is a plus;

  • Experience building microservices, data pipelines and using relational and non-relational databases is a plus;

  • Experience working with data science tooling and deep learning frameworks is a plus;

  • Experience with DevOps engineering (CI/CD pipelines, observability, containers etc) is a plus.

What's in it for you?

  • Be part of a dynamic & flexible working environment;

  • Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;

  • Leaders who support your development through coaching and managing opportunities;

  • Ability to make a difference and lasting impact from a local-to-global scale.

About the AI Group

RBC's AI Group is the AI accelerator for RBC, with a focus on driving the shift from early-stage AI projects to scaled, client outcomes that amplify the impact of RBC's people. In addition to helping scale the biggest AI opportunities at RBC, the AI Group is responsible for advancing research into emerging use cases across generative and agentic AI, while maintaining expertise in security, responsible AI and regulatory expectations. The Business Enablement function within the AI Group partners with LOBs and Functions to set AI ambition, originate transformation opportunities, and frame programs for delivery - ensuring RBC remains at the frontier of AI-enabled value creation.

Inclusion and Equal Opportunity Employment

RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

#Ll-POST

#TechPJ

Job Skills

Big Data Analytics, Critical Thinking, Decision Making, Industry Knowledge, Machine Learning (ML), Software Engineering, Software Product Design

Additional Job Details

Address:

777 BAY ST, TH 27:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

HUMAN RESOURCES & BMCC

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-07-27

Application Deadline:

2026-09-30

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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