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Jr Machine Learning Engineer Jobs in Toronto, ON

Stripe

Machine Learning Engineer

Toronto, ON · On-site

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

Td

Senior Machine Learning Engineer

Toronto, ON · On-site

CA$170K - 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 ...

Td

Machine Learning Engineer II

Toronto, ON · On-site

CA$154K - CA$199K/yr

Day-to-day as a Machine Learning Engineer: * Join a world-class team of AI developers with an extensive track record. * Architect scalable machine learning and Gen AI systems that integrate with ...

OpenTable

Staff Machine Learning Engineer

Toronto, ON · Hybrid

As a Staff Machine Learning Engineer , you will set the technical direction for how OpenTable builds, serves, and operates machine learning systems in production. You will partner with Machine ...

OpenTable

Staff Machine Learning Engineer

Toronto, ON · On-site

As a Staff Machine Learning Engineer ,you will set the technical direction for how OpenTable builds, serves, and operates machine learning systems in production. You will partner with Machine ...

Serve Robotics

Lead Machine Learning Engineer

Toronto, ON · Remote

$225K - $260K/yr

Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline. * Minimum of 5 years of professional experience developing ...

Career Renew

Senior Machine Learning Engineer

Toronto, ON · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

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All JobsJr Machine Learning Engineer JobsJr Machine Learning Engineer Jobs in Toronto, ON

Jr Machine Learning Engineer information

What does a Jr Machine Learning Engineer do?

A Jr Machine Learning Engineer assists in designing, developing, and deploying machine learning models under the guidance of more senior engineers or data scientists. Their responsibilities often include data preprocessing, feature engineering, model training, testing, and helping to integrate models into production systems. They also work on debugging issues, documenting code, and staying up-to-date with the latest industry trends and tools. Junior engineers typically collaborate closely with cross-functional teams to deliver AI-powered solutions.

What are the key skills and qualifications needed to thrive as a Jr Machine Learning Engineer?

To thrive as a Jr Machine Learning Engineer, you need a solid background in mathematics, programming (especially Python), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, as well as experience with data preprocessing and version control systems, is typically required. Strong analytical thinking, problem-solving skills, and the ability to collaborate effectively help you stand out in this role. These competencies are crucial for developing, optimizing, and deploying machine learning models that address real-world business challenges.

What are some common challenges faced by Jr Machine Learning Engineers in their first year on the job?

Jr Machine Learning Engineers often encounter challenges such as understanding complex codebases, managing large datasets, and bridging the gap between academic concepts and real-world applications. Collaboration with data scientists, software engineers, and product teams can also be a learning curve, as effective communication is crucial for project success. Additionally, balancing tasks like model development, testing, and deployment within fast-paced agile environments can be demanding, but these experiences provide valuable opportunities for skill growth and professional development.

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

AspectJr 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 with advanced certifications
Work EnvironmentFocus on developing and deploying ML models, coding, and data preprocessingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, consulting, research institutions

The Jr Machine Learning Engineer primarily develops and deploys ML models, requiring coding skills and familiarity with ML frameworks. Data Scientists analyze data, build statistical models, and interpret insights. While both roles work with data, the Jr Machine Learning Engineer is more focused on implementation, whereas Data Scientists focus on analysis and strategy.

How much do junior machine learning engineers make?

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

What cities near Toronto, ON are hiring for Jr Machine Learning Engineer jobs?

Cities near Toronto, ON with the most Jr Machine Learning Engineer job openings:

Infographic showing various Jr Machine Learning Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Machine Learning Engineer

Toronto, ON • On-site

Stripe
Software Development • 1 - 5K employees
Learn more about Stripeexternal

Full-time

Re-posted 6 days ago

Job description

Who we areAbout Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies-from the world's largest enterprises to the most ambitious startups-use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

Our Applied ML team aims to reform how our users interact with Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include helping our users resolve issues with Stripe faster or making it easier for our users to sign up and navigate Stripe. We are using the latest LLMs as well as fine-tuning our own models. We're an end-to-end team going from ideas to models to shipping in production. You can learn more about our team's work from this recent talk.

What you'll do

As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to production. You will also have the opportunity to contribute to and influence ML architecture at Stripe as well as be a part of a larger ML community.

Responsibilities

Our team operates fluidly and here are some problems you may tackle:

  • How do we evaluate a system offline & online?
  • How do we improve performance to match (and beat) humans?
  • How do we ensure model quality doesn't degrade online?
  • Does fine-tuning an LLM give us better performance?
  • What are the right OSS and in-house platforms we should invest in?

And in the process you will:

  • Develop pipelines and automated processes to train and evaluate models in offline and online environments
  • Integrate ML models into production systems and ensure their scalability and reliability
  • Collaborate with product and strategy partners to propose, prioritize, and implement new product features
  • Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions
Who you are

We are looking for ML Engineers who are passionate about using ML to improve products and delight customers. You have experience developing streaming feature pipelines, building ML models, and deploying them to production, even if it involves making substantial changes to backend code. You are comfortable with ambiguity, love to take initiative, and have a bias towards action.

Minimum requirements
  • Have at least 3 years of experience shipping ML systems in production
  • Hold yourself and others to a high bar when working with production systems
  • Take pride in taking ownership and driving projects to business impact
  • Thrive in a collaborative environment
Preferred qualifications
  • 5+ years of experience in full time software development roles
  • Experience shipping LLM integrations to user products with high quality
  • Experience operating in highly ambiguous environments
  • Knowledge about driving a hypothesis from data

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