PhD Machine Learning Engineer, Intern

Posted 2 Days Ago
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Francis Corners, Town of Malta, NY, USA
In-Office
Internship
Payments • Software
The Role
Develop, train, improve, and deploy large-scale machine learning systems for fraud detection, support, user behavior prediction, and financial infrastructure. Interns will work across the full ML lifecycle, collaborate with cross-functional teams, learn unfamiliar systems, and contribute production-quality code. The role requires pursuing a relevant PhD and returning to the degree program after the internship.
Summary Generated by Built In
Who we areAbout 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 doAbout 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 areMinimum 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.

Skills Required

  • Pursuing a PhD in Computer Science, Machine Learning, or a closely related field
  • Expected graduation in winter 2027 or spring/summer 2028
  • Deep understanding of computer science
  • Practical experience with programming and machine learning through projects, coursework, or research
  • Familiarity with Python, Scala, Spark, Pandas, NumPy, and scikit-learn
  • Expertise in supervised and unsupervised learning techniques
  • Knowledge of machine learning operations
  • Collaborative project experience and ability to apply stakeholder feedback
  • Ability to learn unfamiliar systems and understand complex systems independently
  • Intent to return to the degree program after completing the internship
  • Two years of university education or equivalent experience with in-depth machine learning knowledge
  • Published and presented peer-reviewed articles in top-tier venues
  • Experience writing high-quality pull requests and maintaining test coverage
  • Experience navigating new codebases and working across programming languages
  • Excellent written communication skills

Stripe Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Stripe and has not been reviewed or approved by Stripe.

  • Fair & Transparent Compensation — Pay is commonly characterized as good, competitive, or above market, making compensation a standout aspect. High performers in particular often view overall pay favorably.
  • Equity Value & Accessibility — Equity grants and, depending on role, bonuses or commissions contribute meaningfully to total compensation. Equity is frequently highlighted alongside salary as a strength.
  • Healthcare Strength — Physical, mental, and medical health coverage and wellness programs are part of the core offering. These benefits are portrayed as comprehensive and competitive.

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The Company
HQ: San Francisco, CA
5,360 Employees
Year Founded: 2010

What We Do

Stripe is a technology company that builds economic infrastructure for the internet. Businesses of every size—from new startups to public companies like Salesforce and Facebook—use the company’s software to accept online payments and run technically sophisticated financial operations in more than 100 countries. Stripe helps new companies get started and grow their revenues, and established businesses accelerate into new markets and launch new business models. Over the long term, Stripe aims to increase the GDP of the internet.

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