PhD Machine Learning Engineer Intern — ML Systems at Scale

Wwshemi; San Francisco, New York, Seattle (CA, NY, WA); On-site; USD 33,000 - 67,000; Part time

Job summary

Stripe offers a PhD-level ML internship across Applied ML, Data Science, Risk, and Payments for the summer of 2027. Interns will work on foundational models like Stripe Assistant and Stripe Foundation Model, aiming to improve fraud detection, user behavior prediction, and support enhancements.

You will tackle problems at the intersection of finance, tech, and data, developing production-scale ML systems and collaborating with multiple teams.

Qualifications

• Pursuing a PhD in Computer Science, ML, or a closely related field with expected graduation Winter 2027 or Spring/Summer 2028.
• Practical experience with programming and ML demonstrated via projects, coursework, or research; familiarity with Python, Scala, Spark, Pandas, NumPy, and Scikit-learn.
• Expertise in ML areas such as supervised/unsupervised learning, ML ops, and possibly LLMs or RL.
• Demonstrated collaboration skills and ability to learn new systems independently.

Responsibilities

• Develop and deploy large-scale ML systems that drive significant business value across domains.
• Engage in the end-to-end design, training, improvement, and deployment of ML models.
• Write production-scale ML code deployed to enable economic infrastructure access for diverse global businesses.
• Collaborate across teams to incorporate feedback and proactively find solutions to challenges.
• Rapidly learn new technologies and communicate progress effectively.

Skills

Python

Scala

Spark

Pandas

NumPy

Scikit-learn

Education

PhD in Computer Science or ML

Tools

TensorFlow

PyTorch

Spark ML

HuggingFace

Job description

Stripe offers a PhD-level ML internship across Applied ML, Data Science, Risk, and Payments for the summer of 2027. Interns will work on foundational models like Stripe Assistant and Stripe Foundation Model, aiming to improve fraud detection, user behavior prediction, and support enhancements.

You will tackle problems at the intersection of finance, tech, and data, developing production-scale ML systems and collaborating with multiple teams.