Toronto, Canada
Open 4 months, first seen by us 128 days agoSet the technical and process direction for the ML team based on business goals
Drive an AI/ML vision that benefits users
Brainstorm and coordinate product integrations with partner teams
Hire and develop a team to deliver high-quality ML systems
Coach engineers to grow their careers and keep a high bar
Setting the technical & process direction for the team based on business goals
Driving an ambitious vision for AI/ML that benefits our users
Brainstorm and coordinate product integrations with partner teams
Hire & develop a world-class team to deliver high-quality ML systems.
Coach engineers to help them grow in their careers and maintain a high bar
Have at least 4 years of experience managing ML teams
Experience working as a Machine Learning Engineer, Applied Scientist or equivalent Individual Contributor.
Have experience building & shipping ML systems.
You have experience leading teams that develop streaming feature pipelines, build ML models, and deploy them to production
Hold yourself and others to a high bar when working with production systems.
Experience in shipping LLM & RAG systems
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
Open 4 monthsWe first saw this posting 128 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 128
Up longer than most. Similar jobs usually come down between day 8 and day 76.
Well past Stripe’s usual: its jobs come down by about day 60.
From 5,517 similar postings that came down, and 46 of Stripe’s. Coming down is not always a hire.
35 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.
The newly formed Conversation Platform team aims to build a conversation platform for all merchants who use Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include customizing the Stripe landing page to suggest bespoke integrations, allowing users to command the Stripe API in natural language, and resolving user issues automatically. We are developing RAG based systems on 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.
We are looking for ML Engineering Managers who are passionate about using ML to improve products and delight customers. You have experience leading teams that develop streaming feature pipelines, build ML models, and deploy 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.
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Toronto, Canada
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