PhD ML Engineer Internship - Build Foundation Models

Stripe, Inc.; Menlo Park, San Francisco, New York (CA, CA, NY); Presencial; USD 55.000 - 72.000; Tempo integral

Resumo da vaga

Stripe is seeking PhD machine learning interns for the summer of 2027 to contribute to Stripe's foundation models and ML systems across fraud detection, support, and user behavior prediction. You will build and deploy large-scale ML solutions in a finance tech context with real product impact.

This internship offers hands-on experience with the Stripe Assistant and the Stripe Foundation Model, collaborative projects across Applied ML, Data Science, Risk, and Payments, and mentorship from

Qualificações

• PhD candidate in Computer Science, ML, or related field, graduating winter 2027 or spring/summer 2028.
• Practical ML experience via courses, projects, or research with Python, Scala, Spark.
• Familiarity with ML methods, supervised/unsupervised learning, MLOps, or LLMs/RL.
• Ability to collaborate and apply feedback from multiple stakeholders.
• Self-driven to learn unfamiliar systems and communicate progress.

Responsabilidades

• Develop and deploy large-scale ML systems with business impact across domains.
• Design, train, improve, and launch ML models end-to-end.
• Write production-grade ML models for Stripe's financial infrastructure.
• Collaborate with teams to incorporate feedback and solve challenges.
• Demonstrate proactive learning and clear communication of status.

Conhecimentos

Python

Scala

Spark

Pandas

NumPy

Scikit-learn

ML Ops

LLMs

Reinforcement Learning

Formação

PhD in Computer Science

Ferramentas

Git

GitHub

Descrição da vaga

Stripe is seeking PhD machine learning interns for the summer of 2027 to contribute to Stripe's foundation models and ML systems across fraud detection, support, and user behavior prediction. You will build and deploy large-scale ML solutions in a finance tech context with real product impact.

This internship offers hands-on experience with the Stripe Assistant and the Stripe Foundation Model, collaborative projects across Applied ML, Data Science, Risk, and Payments, and mentorship from