PhD, Machine Learning Engineer, Intern

San Francisco, Seattle

Stripe

Stripe powers online and in-person payment processing and financial solutions for businesses of all sizes. Accept payments, send payouts, and automate financial processes with a suite of APIs and no-code tools.

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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 organization is excited to offer PhD machine learning engineering internships for the summer of 2025. 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

We're Looking for Someone Who Has:

  • 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 2025 or spring/summer 2026.
  • Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Ruby, JavaScript, Scala, and Go is beneficial, but not required.
  • 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.

Preferred qualifications

You Might Also Have:

  • Two years of university education or equivalent experience, with in-depth knowledge in specific domains of machine learning.
  • 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.

Hybrid work at Stripe

Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.

Pay and benefits

The annual US base salary range for this role is $143,000 - $174,200. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.

Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.

We look forward to hearing from you

At Stripe, we're looking for people with passion, grit, and integrity. You're encouraged to apply even if your experience doesn't precisely match the job description. Your skills and passion will stand out—and set you apart—especially if your career has taken some extraordinary twists and turns. At Stripe, we welcome diverse perspectives and people who think rigorously and aren't afraid to challenge assumptions. Join us.
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Tags: Computer Science Engineering Finance GitHub JavaScript LLMs Machine Learning ML models PhD Reinforcement Learning Research Ruby Scala Unsupervised Learning

Perks/benefits: 401(k) matching Career development Equity / stock options Health care Salary bonus Wellness

Region: North America
Country: United States

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