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Machine Learning Engineer

Toronto

Pay
Pay not listed
Work setting
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Employment
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Apply at Stripe

What you’ll work on

Full posting
  • Train and evaluate ML models offline and online

  • Integrate ML models into production systems for scale and reliability

  • Analyze opportunities, propose ideas and run experiments

  • Partner with product and strategy to build new product features

From the employer’s posting
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
analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to production
Collaborate with product and strategy partners to propose, prioritize, and implement new product features

What you’ll bring

All qualifications

Core experience

  • At least 3 years shipping ML systems in production
  • Experience developing streaming feature pipelines
  • Takes ownership and drives projects to business impact
  • Holds production systems to a high bar

Preferred experience

  • 5+ years of full-time software development experience
  • Experience shipping LLM integrations to user products with high quality
  • Experience operating in highly ambiguous environments
Qualification wording
Have at least 3 years of experience shipping ML systems in production
You have experience developing streaming feature pipelines, building ML models, and deploying them to production
Take pride in taking ownership and driving projects to business impact
Hold yourself and others to a high bar when working with production systems
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

About Stripe

Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead.

In the employer’s words · Read in context

Posting record

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Open 3 monthsWe first saw this listing 104 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jul 13, 2026 · 104 days ago
Recorded sightings
214
Last seen by us
Oct 25, 2026

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Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the pay range before committing time to the process.

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Job description

View original posting ↗

Who we are

About 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
Source details

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Location & working pattern

Toronto

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