PhD Machine Learning Engineer Intern

What you'll do

• Develop and deploy large-scale machine learning systems that drive business value across various domains.
• Design, train, improve, and launch machine learning models through the end-to-end development process.
• Write production-scale ML models to enable global economic infrastructure access for diverse businesses.
• Contribute to projects involving foundation models for fraud detection, support, and user behavior prediction.
• Work on creative projects like the Stripe Assistant and the Stripe Foundation Model.
• Navigate new codebases and manage work across different programming languages.
• Write high-quality pull requests and maintain good test coverage for all projects.

What we're looking for

• Pursuing a PhD in Computer Science, Machine Learning, or a related field with an expected graduation in winter 2027 or spring/summer 2028.
• Practical experience with programming and machine learning through projects, classwork, or research.
• Familiarity with Python, Scala, Spark, Pandas, NumPy, and Scikit-learn.
• Expertise in supervised and unsupervised learning techniques, ML operations, and potentially Large Language Models or Reinforcement Learning.
• Demonstrated ability to work on collaborative projects and apply feedback from various stakeholders.
• Proactive ability to learn unfamiliar systems and understand complex systems independently.
• Intent to return to the degree program after the completion of the internship.
• Two years of university education or equivalent experience with in-depth knowledge in specific domains of machine learning (preferred).
• Published and presented peer-reviewed articles in top-tier venues (preferred).
• Experience writing high-quality pull requests, maintaining test coverage, and navigating new codebases (preferred).
• Excellent written communication skills to articulate work to team members and wider audiences (preferred).