Machine Learning Engineer

Stripe • Toronto, ON

31d

About The Position

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.

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.

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.

Requirements

• 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

Nice To Haves

• 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

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
• Engage with the latest developments in ML/AI and take calculated risks in transforming innovative ML ideas into productionized solutions

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed