Machine Learning Engineer

Stripe is hiring a Machine Learning Engineer in Toronto, Canada. Level rates it ; you can apply on Stripe.

Level's read on this job

Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include Python, PyTorch and LLMs.
Level classifies it as a mid-level role.
Level lists 720 other open roles at Stripe.

AI in this role

Build and deploy machine learning models and LLM solutions into production to automate and assist user tasks at Stripe.

pythonpytorchllms

llm-integrationfine-tuningmachine-learningmlopsmodel-trainingfeature-pipelines

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

How we rate this

Machine Learning Engineer at Stripe rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Machine Learning Engineer is an open job at Stripe.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in Toronto.
The job was posted on July 10, 2026.
Seniority: mid.
Applications are handled by Stripe. Apply on Stripe

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

LLM IntegrationFine-tuningMachine learningMLOpsModel TrainingFeature PipelinesPythonPyTorch

Also common in machine learning engineer jobs at this level

Python PyTorch TensorFlow Deep learning AWS Generative AI

Pay

Typical machine learning engineer job: $199k

This posting doesn't list pay. Use the typical machine learning engineer figure when pay comes up. See machine learning engineer jobs

Questions you could be asked

How have you integrated a large language model into a production application?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where mlops was part of your work. What did you do?
Tell me about a project where model training was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: LLM Integration, Fine-tuning, Machine learning, MLOps, and Model Training. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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