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
The newly formed Productivity ML Accelerator team aims to reform productivity across 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 data scientists to write SQL queries. 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.
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:
- Which Text2SQL algorithm should we implement? What are the tradeoffs?
- 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?
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
- At least 5 years of industry experience doing end-to-end ML development on a machine learning team and bringing ML models to production
- Advanced degree in a quantitative field (e.g. computer science, statistics, physics, …)
- Proficient in Python, Scala, Spark
Preferred qualifications
- Knowledge about how to manipulate data to perform analysis, including querying data, defining metrics, or slicing and dicing data to evaluate a hypothesis.
- Experience evaluating niche and upcoming ML solutions
Jobs from our Partners
Software Engineer I (Cloud, Web, API, AWS)
Sr Principal Digital Signal Processing (DSP) Firmware Engineer
Cloud Engineer
System Integration and Test Engineer
Senior Software Engineer - C++ / Python
Other Jobs from Stripe
Staff Software Engineer, Compute
Full Stack Engineer, WPP
Frontend Engineer, WPP
Staff Machine Learning Engineer, ML Foundations (Technical Leader)
Staff Engineer, ML Foundations (Technical Leader)
Similar Jobs
Lead Data Scientist
Lead Data Engineer - Samsung Ads
Lead Data Scientist
Data Management Senior Lead - Data Engineering Architect (Cloud)
Senior Data Engineer
Staff Machine Learning Engineer
There are more than 50,000 engineering jobs:
Subscribe to membership and unlock all jobs
Engineering Jobs
50,000+ jobs from 4,500+ well-funded companies
Updated Daily
New jobs are added every day as companies post them
Refined Search
Use filters like skill, location, etc to narrow results
Become a member
🥳🥳🥳 251 happy customers and counting...
Overall, over 80% of customers chose to renew their subscriptions after the initial sign-up.
Cancel anytime / Money-back guarantee