PhD Machine Learning Engineering Internship
Are you applying to the internship?
Job Description
About Stripe:
Stripe is a financial infrastructure platform serving millions of businesses globally, ranging from large enterprises to startups. Their mission is to increase the GDP of the internet. They offer tools for businesses to accept payments, grow revenue, and explore new business opportunities.
Job Description: PhD Machine Learning Engineering Internship (Summer 2025)
Stripe’s Applied ML organization is seeking PhD students for a summer 2025 internship. This role offers the chance to contribute to impactful projects directly improving Stripe’s product suite. The focus is on foundation models applied to tasks including fraud detection, enhanced customer support, and user behavior prediction.
Responsibilities:
• Develop and deploy large-scale machine learning systems that deliver significant business value across various domains.
• Manage the entire lifecycle of machine learning models: design, training, improvement, and launch.
• Build production-scale ML models to improve Stripe’s global economic infrastructure access for diverse businesses.
• Collaborate effectively with cross-functional teams, incorporating feedback and proactively solving problems.
• Quickly learn new technologies and approaches, demonstrating insightful questioning and clear communication of work progress.
Qualifications:
Minimum Requirements:
• Pursuing a PhD in Computer Science, Machine Learning, or a related field, graduating in Winter 2025 or Spring/Summer 2026.
• Practical machine learning and programming experience (projects, coursework, research). Familiarity with Python, Scala, Spark, Pandas, NumPy, and Scikit-learn.
• Expertise in supervised and unsupervised learning, ML operations, and potentially Large Language Models or Reinforcement Learning.
• Proven ability to collaborate on projects and effectively utilize feedback.
• Proactive approach to learning new systems and independently understanding complex systems.
Preferred Qualifications:
• Two years of university education or equivalent experience with in-depth knowledge in specific ML domains.
• Experience writing high-quality pull requests, maintaining good test coverage, and completing projects with minimal defects.
• Skill in navigating new codebases and managing work across multiple programming languages.
• Excellent written communication skills for conveying work effectively to both team members and broader audiences.
Application Requirements:
• Detailed resume or LinkedIn profile.
• Examples of relevant work and learning approach (GitHub repositories, Stack Overflow contributions, project portfolios).
