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Entry Level Machine Learning Jobs in North York, ON

BMO Capital Markets

Cloud/AI Platform Engineer

Toronto, ON

CA$75K - CA$141K/yr

  • Medical

  • Life

  • Retirement

New Graduate / Entry Level About the Role Are you looking to make your mark in AI? Are you an AI ... Build and maintain cloud-native platform services that support AI and machine learning workloads.

New

Randstad Canada

Cloud/AI Platform Engineer

Toronto, ON · On-site

CA$75K - CA$141K/yr

  • Medical

  • Life

  • Retirement

New Graduate / Entry Level About the Role Are you looking to make your mark in AI? Are you an AI ... Build and maintain cloud-native platform services that support AI and machine learning workloads.

New

Westlake

Electrician - Afternoons

Woodbridge, ON · On-site

$44.23/hr

  • Retirement

  • PTO

Training & Development - Access to multiple platforms of learning (online, in person, 3rd party ... Program/ machinery and processes within the company. * Support and work within the procedures of ...

Westlake

Electrician

Woodbridge, ON

$45.56/hr

  • Retirement

  • PTO

Training & Development - Access to multiple platforms of learning (online, in person, 3rd party ... Program/ machinery and processes within the company. * Support and work within the procedures of ...

Nestle

Marketing Associate

North York, ON · Hybrid

  • Medical

  • Dental

  • Retirement

  • PTO

Demonstrated learning agility and adaptability in a fast-paced environment. * Ability to work ... Up to 50% off - Nespresso Coffee Machine, Capsules and accessories * Access to the Discount Company ...

All JobsMachine Learning JobsEntry Level Machine Learning JobsEntry Level Machine Learning Jobs in North York, ON

Entry Level Machine Learning information

See North York, ON salary details

$20.7K

$67.5K

$157.1K

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

As of Aug 19, 2026, the average yearly pay for entry level machine learning in North York, ON is $67,473.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,562.00 and $84,764.00 per year, depending on experience, location, and employer.

What are entry level machine learning jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

What types of projects can an entry level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

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

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio. Internships, certifications, and participating in competitions like Kaggle can also improve your chances of entering the field without prior experience.
More about Entry Level Machine Learning jobs

What job categories do people searching Entry Level Machine Learning jobs in North York, ON look for?

The top searched job categories for Entry Level Machine Learning jobs in North York, ON are:

What cities near North York, ON are hiring for Entry Level Machine Learning jobs?

Cities near North York, ON with the most Entry Level Machine Learning job openings:

Entry Level Machine Learning jobs near you

Cloud/AI Platform Engineer

BMO Capital Markets

Toronto, ON

CA$75K - CA$141K/yr

Full-time

Medical, Life, Retirement

Posted 2 days ago

New

Job description

Application Deadline:

08/29/2026

Address:

4100 Gordon Baker Road

Job Family Group:

Technology
AI Platform Engineer (New Graduate)

Location: Toronto, ON (Hybrid)
Job Type: Full-Time
Experience Level: New Graduate / Entry Level

About the Role

Are you looking to make your mark in AI? Are you an AI thought leader?

We are seeking a passionate and curious AI Platform Engineer (New Graduate) to help build, operate, and scale the next generation of AI infrastructure and platforms. This role is ideal for recent university graduates who are excited about cloud computing, artificial intelligence, machine learning platforms, developer tools, and large-scale distributed systems.

It's an opportunity that can make you an AI leader at BMO.

As an AI Platform Engineer, you will work with experienced engineers and data scientists to create reliable, secure, and scalable platforms that enable AI applications and machine learning workloads across the organization.

This is an opportunity to learn from industry experts while contributing to cutting-edge AI solutions that drive real business impact.

What You'll Do
  • Build and maintain cloud-native platform services that support AI and machine learning workloads.
  • Design and implement automation solutions using Infrastructure as Code (IaC).
  • Develop tools, APIs, and services that improve developer productivity and platform reliability.
  • Assist in deploying, monitoring, and scaling AI models and machine learning pipelines.
  • Collaborate with software engineers, data scientists, and product teams to operationalize AI solutions.
  • Monitor platform health and troubleshoot performance, reliability, and scalability issues.
  • Contribute to CI/CD pipelines and DevOps practices for AI and platform engineering teams.
  • Participate in system design discussions and code reviews.
  • Learn and apply best practices around security, observability, governance, and cloud architecture.
QualificationsRequired
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Computer Engineering, Data Science, or a related technical field completed within the last 12 months.
  • Strong programming skills in one or more languages such as:
    • Python
    • Go
    • Java
    • C#
  • Understanding of software engineering fundamentals, including:
    • Data structures and algorithms
    • Object-oriented design
    • REST APIs
    • Version control (Git)
  • Familiarity with Linux operating systems and scripting.
  • Knowledge of cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
  • Strong problem-solving and analytical skills.
  • Excellent communication and collaboration abilities.
Preferred
  • Exposure to machine learning, generative AI, or large language models through coursework, projects, or internships.
  • Experience with containers and orchestration technologies such as Docker and Kubernetes.
  • Familiarity with MLOps concepts and tools.
  • Understanding of CI/CD practices and automation.
  • Experience with infrastructure-as-code tools such as Terraform.
  • Contributions to open-source projects, hackathons, research, or personal technical projects.
What You'll Learn
  • AI platform architecture and operations at scale.
  • Cloud-native application design and deployment.
  • MLOps, LLMOps, and AI governance best practices.
  • Platform engineering and site reliability engineering principles.
  • Secure software development and enterprise cloud operations.
What We're Looking For

We're looking for individuals who:

  • Are naturally curious and eager to learn.
  • Enjoy solving challenging technical problems.
  • Thrive in collaborative environments.
  • Take ownership of their work and seek continuous improvement.
  • Are excited about the future of AI and cloud technologies.
  • Critical Thinking
  • Building and managing relationships.
  • Adaptability.
  • Verbal & written communication skills.
  • Collaboration & team skills.
  • Analytical and problem solving skills.
  • Data driven decision making.

Nice-to-Have Technical Skills

  • Azure AI Services, Azure Machine Learning, or Azure Kubernetes Service (AKS)
  • Kubernetes, Docker, Helm
  • Terraform or Bicep
  • GitHub Actions or Azure DevOps
  • Prometheus, Grafana, OpenTelemetry
  • PostgreSQL, Redis, or NoSQL databases
  • LangChain, Semantic Kernel, or other AI frameworks
  • Retrieval-Augmented Generation (RAG) concepts

Salary:

$75,900.00 - $141,900.00

Pay Type:

Salaried

The above represents BMO Financial Group's pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group's expected target for the first year in this position.

BMO Financial Group's total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit:https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one - for yourself and our customers. We'll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we'll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other's differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

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