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Machine Learning Engineer Intern Jobs in Toronto, ON

Experience: 7+ years of industry experience in software engineering with a strong focus on applied machine learning, deep learning, or NLP. * Programming Mastery: Expert-level proficiency in Python ...

Your Role As an AI / Machine Learning Engineer at Thri5, you'll help build the agent layer that powers our System of Actions. You'll design and implement multi-agent Co-pilot systems that orchestrate ...

We are seeking a motivated Software Engineer Intern who is eager to gain hands-on experience ... Exposure to AI applications, LLM APIs, or machine learning projects. * Contributions to open-source ...

... Engineer to join our AI/ML Platform team. This role is pivotal in ensuring the smooth operationalization of machine learning models and the overall efficiency of our next-generation AI/ML platform ...

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Showing results 1-20

Machine Learning Engineer Intern information

See Toronto, ON salary details

$21.9K

$115.2K

$205.7K

How much do machine learning engineer intern jobs pay per year?

As of Jul 6, 2026, the average yearly pay for machine learning engineer intern in Toronto, ON is $115,226.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,463.00 and $156,511.00 per year, depending on experience, location, and employer.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

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

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

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 Machine Learning Engineer Intern jobs in Toronto, ON? For Machine Learning Engineer Intern jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Intern jobs in Toronto, ON look for? The top searched job categories for Machine Learning Engineer Intern jobs in Toronto, ON are:
What cities near Toronto, ON are hiring for Machine Learning Engineer Intern jobs? Cities near Toronto, ON with the most Machine Learning Engineer Intern job openings:
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Workday

Toronto, ON

Full-time

Posted 21 days ago


Workday rating

9.2

Company rating: 9.2 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

16th of 202 rated software companies


Job description

Your work days are brighter here.

We're obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we're shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you'll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We're in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you'll do meaningful work with Workmates who've got your back. In return, we'll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you've found a match in Workday, and we hope to be a match for you too.

About the Team

At Workday AI Team, we are building the intelligence layer that powers the future of work for millions of global users. Our AI organization is responsible for seamlessly embedding cutting-edge machine learning, Generative AI, and autonomous agents directly into Workday's core platform-optimizing the HR and financial operations of some of the world's largest enterprises. We don't just run sandbox experiments; we build robust, production-grade AI solutions that solve real business challenges at global scale.As part of our team, you will operate at the intersection of deep applied research and scalable engineering. Whether we are developing sophisticated LLM-powered agents, advancing our next-generation AI engine (Workday Illuminate), or engineering highly precise information retrieval and recommendation systems, we leverage Workday's massive, clean, and exclusive datasets to deliver features that accelerate human workflows.We are a highly collaborative, cross-functional group of product leaders, data scientists, and ML engineers committed to the principles of Responsible AI. If you are a curious, courageous builder who wants to transition emerging AI capabilities into high-impact enterprise realities, you'll find a home with us.

About the Role

What you will do:

  • Architect & Build: Design, develop, and deploy scalable machine learning models and AI systems (ranging from predictive models to Generative AI and LLM-powered agents) that directly impact Workday's core enterprise applications.

  • End-to-End Ownership: Take full ownership of the ML lifecycle, including data extraction, feature engineering, model training, deployment, optimization, and continuous monitoring in a high-scale production environment.

  • Cross-Functional Collaboration: Partner closely with Data Scientists, Software Engineers, Product Managers, and UX Designers to translate complex business problems into robust AI solutions.

  • Drive Technical Excellence: Establish and advocate for engineering best practices, robust MLOps processes, and highly optimized code.

  • Mentorship & Leadership: Guide and mentor junior engineers, conduct code and architecture reviews, and help shape the technical roadmap for your team.

  • Champion Responsible AI: Ensure all models adhere to Workday's strict standards for data privacy, security, fairness, and ethical AI practices.

About You

Basic Qualifications

  • Experience: 7+ years of industry experience in software engineering with a strong focus on applied machine learning, deep learning, or NLP.

  • Programming Mastery: Expert-level proficiency in Python and strong software engineering fundamentals (data structures, algorithms, object-oriented design).

  • ML Frameworks: Deep hands-on experience with industry-standard machine learning and deep learning libraries (e.g., PyTorch, TensorFlow, Scikit-learn, Hugging Face).

  • Production Deployment: Proven track record of taking ML models out of research/notebook environments and deploying them into scalable, high-traffic production systems.

  • Cloud & Infrastructure: Solid experience with cloud computing platforms (AWS or GCP) and modern infrastructure tools (Docker, Kubernetes).

  • Education: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related highly quantitative field (or equivalent practical experience).


Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.

Primary Location: CAN.ON.TorontoPrimary CAN Base Pay Range: $156,000 - $234,000 CADAdditional CAN Location(s) Base Pay Range: $156,000 - $234,000 CAD


Our Approach to Flexible Work

With Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.


At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email accommodations@workday.com.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

At Workday, we value our candidates' privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.


What Workday employees say

Pay

Hours and flexibility

Workplace

Get the full story on Breakroom


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About Workday

Sourced by ZipRecruiter

Workday's journey began with a transformative idea generated during a breakfast conversation between its founders in sunny California. What set us apart from the start was our people-centric culture, driven by the core value of prioritizing our employees. At Workday, the happiness, growth, and contributions of every team member are at the heart of who we are. Our collaborative and employee-focused culture is the key ingredient for our business success. We not only care for our people but also for the communities and the environment, all while maintaining profitability. Embrace your uniqueness, as we encourage our Workmates to shine brightly in their authentic selves. Our passion and energy make us distinct, and we are inspired to create a brighter workday for everyone.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

Pleasanton, CA, US

Year founded

2005