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Junior Machine Learning Engineer Jobs in Ontario

What We're Looking For We're looking for a junior machine learning engineer to join our team and grow into a strong, hands‑on ML engineer. This is a role for someone early in their career who is ...

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 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 · On-site

$120 - $250/hr

We are currently seeking talented individuals for a variety of positions, ranging from junior to ... As a Machine Learning Engineer, you will:Join a world-class team of AI developers with an extensive ...

We are currently seeking talented individuals for a variety of positions, ranging from junior to ... As a Machine Learning Engineer, you will: * Join a world-class team of AI developers with an ...

$85 - $110/hr

Job Responsibilities The Machine Learning Engineer will play a pivotal role in driving innovation and operational efficiency through data‑driven solutions leveraging machine learning and artificial ...

Machine Learning Engineer

Toronto, ON · On-site

$80 - $120/hr

About the Opportunity We are looking for a talented Machine Learning Engineer to join our team and deliver machine learning-driven products. The right candidate will work on development, deployment ...

Machine Learning Engineer

Toronto, ON · Hybrid

CA$152K - CA$174K/yr

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 ...

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 ...

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

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.

Machine Learning Engineer

Toronto, ON · On-site

$129.20 - $174.80/hr

We are seeking a Machine Learning Engineer to join our growing engineering team. This role is open to candidates across Canada (excluding Quebec). Local candidates in Burnaby, Calgary, or Toronto ...

Machine Learning Engineer

Toronto, ON · On-site

$110 - $180/hr

What you'll doAs a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to ...

New

Machine Learning Engineer

Toronto, ON · On-site

$118.80 - $148.50/hr

Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world's best transportation solutions. We tackle a wide range of challenges, from pricing and ...

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Showing results 1-20

Junior Machine Learning Engineer information

See Ontario salary details

$26K

$119.2K

$207.5K

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

As of Jul 16, 2026, the average yearly pay for junior machine learning engineer in Ontario is $119,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,500.00 and $149,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a Junior Machine Learning Engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What is the difference between Junior Machine Learning Engineer vs Data Scientist?

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What does a junior machine learning engineer do?

A junior machine learning engineer assists in developing, testing, and deploying machine learning models under supervision. They work with data preprocessing, feature engineering, and use tools like Python and libraries such as TensorFlow or scikit-learn to support AI projects. This role often requires foundational knowledge of algorithms, programming, and data analysis.

How much does a junior machine learning engineer make?

A junior machine learning engineer typically earns between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Achieving this level often requires advanced degrees, specialized certifications, and a strong track record of impactful projects.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. These positions usually involve leadership, strategic planning, and significant experience, and they tend to be found in large tech companies or specialized AI firms.

What Does a Junior Machine Learning Engineer Do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

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 Junior Machine Learning Engineer jobs in Ontario? For Junior Machine Learning Engineer jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning Engineer jobs in Ontario look for? The top searched job categories for Junior Machine Learning Engineer jobs in Ontario are:
What cities in Ontario are hiring for Junior Machine Learning Engineer jobs? Cities in Ontario with the most Junior Machine Learning Engineer job openings:
Infographic showing various Junior Machine Learning Engineer job openings in Ontario as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $119,158 per year, or $57.3 per hour.

Junior Machine Learning Engineer

Providius

Hamilton, ON • On-site

$60 - $80/hr

Other

Medical, Dental, Vision, PTO

Posted 29 days ago


Job description

What We’re Looking For

We’re looking for a junior machine learning engineer to join our team and grow into a strong, hands‑on ML engineer.

This is a role for someone early in their career who is eager to learn, comfortable getting their hands dirty with real data, and motivated to build a solid foundation in applied machine learning.

You will work under the direction of senior ML and engineering staff, contributing to real models and pipelines while developing your skills and judgment over time.

Position Overview

Working closely with senior engineers, you will:

  • implement, train, and evaluate models under guidance
  • prepare and explore real-world data
  • help build and maintain data pipelines
  • support experiments and document results
  • 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 you build experience, you will take on more ownership and tackle increasingly open‑ended problems.

Duties and Responsibilities
  • Implement and train models under the guidance of senior engineers
  • Prepare, clean, and explore datasets, including feature engineering
  • Run experiments, record results, and help interpret findings
  • Build and maintain parts of the data pipeline and supporting tooling
  • Help integrate models into larger systems alongside the team
  • Write clear, testable, and maintainable code
  • Ask good questions, seek feedback, and learn from code review
Required Skills / Experience
  • 0–2 years of experience in machine learning, or strong academic or project experience
  • Programming ability in Python
  • Solid grounding in machine learning fundamentals
  • Willingness to work with real-world, imperfect data
  • Strong problem‑solving ability and a desire to learn
  • Ability to take direction and incorporate feedback
  • Clear communication in a team environment
What this Role Requires
  • Eagerness to learn and grow quickly
  • Comfort working with guidance and asking for help when needed
  • Pragmatism and a willingness to see tasks through
  • Attention to detail and care in the work
  • Ownership of your own learning and contributions
Nice to haves
  • Coursework, internships, or projects involving anomaly detection, time‑series, or behavioral modeling
  • Exposure to streaming or telemetry data
  • Familiarity with common ML libraries and tooling
  • Experience contributing to a shared codebase
Benefits
  • Dental care
  • Extended health care
  • On‑site parking
  • Paid time off
  • Vision care
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