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Machine Learning Engineer Intern Jobs in Ontario

Quincus

Machine Learning Engineer

Toronto, ON

As a machine learning engineer, you will be responsible for designing and implementing scalable systems for serving models, optimizing inference performance, and managing production workflows.

NTENT

Machine Learning Engineer

Toronto, ON · Remote

Machine Learning Engineer Position: Full time Location: Toronto, Ontario (Initially Remote) About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize ...

Themis

Machine Learning Engineer

Mississauga, ON · On-site

CA$85K - CA$135K/yr

Machine Learning Engineer About Themis Intelligence Themis Intelligence builds the Utility Knowledge Base (UKB) and Human-Guided Intelligence (HGI) platforms, redefining how utilities operate. Our ...

Machina Labs

Machine Learning Engineer

Chatsworth, ON

CA$160K - CA$190K/yr

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...

Td

Machine Learning Engineer

Toronto, ON

CA$120K - CA$250K/yr

As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an extensive track record of shipping solutions at the cutting-edge * Architect scalable machine learning and ...

Altera

Machine Learning Engineer

Toronto, ON

CA$172.10 - CA$253.70/hr

About the Role We are seeking a Machine Learning Engineer to help drive the development,optimizationand deploymentof Altera FPGA Compiler. In this role, you will work at the intersection of machine ...

Hays

Senior Machine Learning Engineer Hourly Rat e: 80-100/hr Location : Remote Length : 6 month contract (long term potential) Your New Company Our client is a fast-paced, product-led business building ...

United Airlines

Machine Learning Engineer

Toronto, ON · On-site

Active Learning Agile Methodology AI Agents AI Concepts AI Frameworks Application Integrations Detail Oriented Enterprise Application Delivery Group Problem Solving Machine Learning ML Programming ...

Workday

Principal Machine Learning Engineer

Toronto, ON · On-site

About the Role As a Principal Machine Learning Engineer in Agent Factory, you'll design and build the core ML systems behind Workday's next generation of AI agents. Working within a small, senior ...

Omnissa

CA$162.51K - CA$342.75K/yr

As a Staff Machine Learning Engineer , you will design, build, and deploy machine learning systems that power predictive analytics, personalization, automation, and intelligent platform behaviors.You ...

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Machine Learning Engineer Intern information

See Ontario salary details

$23K

$120.7K

$215.5K

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

As of Jun 1, 2026, the average yearly pay for machine learning engineer intern in Ontario is $120,739.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,500.00 and $164,000.00 per year, depending on experience, location, and employer.

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 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.
More about Machine Learning Engineer Intern jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Ontario? The most popular types of Machine Learning Engineer jobs in Ontario are:
What are popular job titles related to Machine Learning Engineer Intern jobs in Ontario? For Machine Learning Engineer Intern jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Intern jobs in Ontario look for? The top searched job categories for Machine Learning Engineer Intern jobs in Ontario are:
What cities in Ontario are hiring for Machine Learning Engineer Intern jobs? Cities in Ontario with the most Machine Learning Engineer Intern job openings:
Machine Learning Engineer Intern jobs near you
Infographic showing various Machine Learning Engineer Intern job openings in Ontario as of May 2026, with employment types broken down into 89% Full Time, 10% Part Time, and 1% Contract. Highlights an 69% Physical, 1% Hybrid, and 30% Remote job distribution, with an average salary of $120,739 per year, or $58 per hour.

Machine Learning Engineer

Quincus

Toronto, ON

Full-time

Posted 26 days ago

Job description

"Make every logistics journey your best one yet"

The Company.
Founded in 2014, Quincus is a B2B supply chain operating SaaS platform headquartered in Singapore. We solve today's global supply chain challenges with groundbreaking technology. Using AI and machine learning, we have digitized and optimized the logistics process while giving customers full transparency into their supply chain. 
 
Quincus was founded by two visionary entrepreneurs who possess more than a decade of experience in tech. Chief Product Officer Katherina-Olivia Lacey is leading a tech revolution in this space while empowering women in the supply chain industry. Jonathan E. Savoir, Chief Executive Officer, appeared on Forbes' 30 Under 30 Asia List in 2020, and also serves on the boards of several startups.  

Overview.
Quincus Research is building the next generation of intelligent systems for all Quincus products. To achieve this, we're working on projects that utilize the latest computer science techniques developed by skilled software engineers and research scientists. Quincus Research teams collaborate closely with other teams across Quincus, maintaining the flexibility and versatility required to adapt new projects and focuses that meet the demands of the world's fast-paced business needs. 

Job Overview. 
We are looking for a highly motivated and experienced machine learning engineer to join our team and help us develop and deploy deep learning and reinforcement learning algorithms at scale. As a machine learning engineer, you will be responsible for designing and implementing scalable systems for serving models, optimizing inference performance, and managing production workflows. 

Responsibilities: 
- Design and implement scalable systems for serving deep learning and reinforcement learning models.
- Optimize inference performance of deep learning and reinforcement learning models using techniques such as quantization, pruning, and distillation.
- Utilize GPU computing to accelerate model training and inference.
- Develop and deploy production workflows for training and serving machine learning models.
- Collaborate with data scientists and software engineers to design and implement machine learning systems.
- Monitor and improve the performance of machine learning models in production.
- Stay up-to-date with the latest research and techniques in deep learning and reinforcement learning. 
 
Qualifications:
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
- 3+ years of experience in software engineering or machine learning engineering.
- Strong programming skills in Python (C++ or Java a plus)
- Experience with deep learning frameworks such as TensorFlow or PyTorch.
- Experience with GPU programming using CUDA, OpenCL, or similar libraries.
- Experience with distributed systems and cloud computing platforms such as Kubernetes, Docker, GCP, and AWS. 

Preferred Qualifications: 
- Ph.D. in Computer Science, Electrical Engineering, or a related field.
- 5+ years of experience in software engineering or machine learning engineering.
- Experience with reinforcement learning algorithms and frameworks.
- Experience with production deployment of machine learning models and implementation of APIs for big data.
- Strong understanding of computer architecture and performance optimization.
- Strong communication and collaboration skills. 

If you are passionate about developing and deploying machine learning algorithms at scale, and want to join a dynamic team working on cutting-edge technology, we encourage you to apply for this position.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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