Machine Learning Engineer

Toronto, CanadaOn-site

Responsibilities

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

Our Applied ML team aims to reform how our users interact with Stripe.
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
What are the right OSS and in-house platforms we should invest in?
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.
experience shipping ML systems in production
experience in full time software development roles •
Experience operating in highly ambiguous environments
Knowledge about driving a hypothesis from data

Thrive in a collaborative environment Preferred [REQUIREMENTS] qualifications 5+ years of

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