Strategic Overview
PhD Machine Learning Engineer, Intern at Stripe is defined by the responsibilities and candidate requirements in the employer's listing.
The published role emphasizes work such as Develop and deploy large-scale machine learning systems that drive significant business value across various domains. Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
The role is listed for San Francisco, New York City, Seattle with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying.
Key information at a glance
About This Role
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.
Key Responsibilities & Objectives
- Develop and deploy large-scale machine learning systems that drive significant business value across various domains.
- Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
- Write production-scale ML models that will be deployed to help Stripe enable economic infrastructure access for a diverse range of businesses globally.
- Collaborate across teams to incorporate feedback and proactively seek solutions to challenges.
Required Qualifications & Candidate Blueprint
- A deep understanding of computer science, obtained through the pursuit of a PhD in Computer Science, Machine Learning, or a closely related field, with the expectation of graduating in winter 2027 or spring/summer 2028.
- Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Python, Scala, Spark and libraries such as Pandas, NumPy, and Scikit-learn.
- Expertise in areas of machine learning such as supervised and unsupervised learning techniques, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
Salary & Benefits
The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
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.
What you’ll do
About the internship
Stripe's Applied ML, Data Science, Risk, and Payments organizations are excited to offer PhD machine learning engineering internships for the summer of 2027. This is an exceptional opportunity to contribute to critical projects that directly enhance Stripe's suite of products, focusing on areas such as foundation models used for dozens of tasks e.g. fraud detection, enhanced support, and predicting user behavior.
As an intern, you'll tackle challenging problems at the intersection of finance, technology, and data. You'll have the chance to work on creative projects like the Stripe Assistant and the Stripe Foundation Model, which leverage machine learning to revolutionize how businesses interact with financial services and data.
Responsibilities
- Develop and deploy large-scale machine learning systems that drive significant business value across various domains.
- Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
- Write production-scale ML models that will be deployed to help Stripe enable economic infrastructure access for a diverse range of businesses globally.
- Collaborate across teams to incorporate feedback and proactively seek solutions to challenges.
- Rapidly learn new technologies and approaches, demonstrating a strong ability to ask insightful questions and communicate the status of your work effectively.
Who you are
Minimum requirements
- A deep understanding of computer science, obtained through the pursuit of a PhD in Computer Science, Machine Learning, or a closely related field, with the expectation of graduating in winter 2027 or spring/summer 2028.
- Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Python, Scala, Spark and libraries such as Pandas, NumPy, and Scikit-learn.
- Expertise in areas of machine learning such as supervised and unsupervised learning techniques, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
- Demonstrated ability to work on collaborative projects, with experience in receiving and applying feedback from various stakeholders.
- A proactive approach to learning unfamiliar systems and a demonstrated ability to understand complex systems independently.
- Intent to return to the degree-program after the completion of the internship/co-op.
Preferred qualifications
You Might Also Have:
- Two years of university education or equivalent experience, with in-depth knowledge in specific domains of machine learning.
- Published and presented peer-reviewed articles in top-tier venues.
- Experience in writing high-quality pull requests, maintaining good test coverage, and completing projects with minimal defects.
- Familiarity with navigating new codebases and managing work across different programming languages.
- Excellent written communication skills to clearly articulate your work to both team members and wider Stripe audiences.
Application requirements
Please submit the following with your application:
- A detailed resume or LinkedIn profile showcasing your work history.
- Examples of relevant work and your approach to learning, such as GitHub repositories, StackOverflow contributions, or other project portfolios.
Join us for an unforgettable summer internship and help shape the future of global commerce. At Stripe, you won't just be working on theoretical projects; you'll make a tangible impact on the world's economic infrastructure.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This opening may suit candidates whose experience matches the role-specific capabilities named in the listing. Its strongest career signal is the scope of the work itself — particularly Develop and deploy large-scale machine learning systems that drive significant business value across various domains. — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground the role-specific capabilities named in the listing, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
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