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Machine Learning Engineer Intern Jobs in Ontario

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.

Machine Learning Engineer

Toronto, ON · Remote

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

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 ...

Machine Learning Engineer

Toronto, ON · Hybrid

CA$129K - CA$174K/yr

  • Medical

  • Dental

  • Vision

We are currently seeking a Machine Learning Engineer to join our rapidly growing engineering team. This role is for someone who is passionate about building innovative solutions and being exposed to ...

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 ...

Machine Learning Engineer

Toronto, ON · On-site

$100 - $130/hr

  • Dental

  • Vision

  • PTO

Apply machine learning design patterns to build modular, reusable, and production-ready models. * Collaborate with data engineers to develop high-performance data pipelines for training and inference.

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 ...

Junior Machine Learning Engineer

Waterloo, ON · On-site

CA$80K - CA$95K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Junior Machine Learning Engineer on the Global AI Team, you will support the design, development, deployment, and maintenance of AI and machine learning solutions. You will work with data ...

Junior Machine Learning Engineer

Hamilton, ON · On-site

  • Medical

  • Dental

  • Vision

  • PTO

This role is hands-on and engineering-focused. You will be writing code, working with messy, real-world data, and learning how machine learning systems are built and run in practice. Over time, as ...

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

Advanced programming skills in Python, with practical experience using popular machine learning libraries such as scikit-learn, TensorFlow, and/or PyTorch. Capable of building, tuning, and deploying ...

We are looking for a Sr. Machine Learning Engineer to help translate raw data into meaningful insights that drive strategic decision-making. The Opportunity Summary We are seeking an experienced ...

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 ...

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Showing results 1-20

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 Aug 15, 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 do machine learning engineer interns do?

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?

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 skills and qualifications are needed to thrive as a machine learning engineer intern?

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 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:

Infographic showing various Machine Learning Engineer Intern job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 66% Full Time, 30% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $120,739 per year, or $58 per hour.

Machine Learning Engineer

Quincus

Toronto, ON

Full-time

Re-posted 11 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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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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