PhD ML Engineer Intern — Large-Scale Systems

Stripe, Inc.; Seattle (WA); On-site; USD 130,000 - 169,000; Full time

Job summary

Stripe, Inc. is offering PhD machine learning engineering internships for the summer of 2027. This is a unique chance to contribute to critical projects that enhance Stripe's products, including foundation models used for fraud detection, support, and predicting user behavior.

You will tackle challenging problems at the intersection of finance, technology, and data, working on projects like the Stripe Assistant and the Stripe Foundation Model, with collaboration across teams.

Qualifications

• Pursuing a PhD in Computer Science, ML, or related field with expected graduation winter 2027 or spring/summer 2028.
• Practical programming and ML experience with Python, Scala, Spark, and Pandas/NumPy/Scikit-learn.
• Expertise in ML areas such as supervised/unsupervised learning, ML ops, possibly LLMs or RL.
• Ability to work on collaborative projects and apply feedback from stakeholders.
• Proactive learner with ability to understand complex systems independently.
• Intent to return to degree program after the internship/co-op.

Responsibilities

• Develop and deploy large-scale ML systems that drive significant business value.
• End-to-end design, training, improving, and launching ML models.
• Write production-scale ML models deployed to enable economic infrastructure access globally.
• Collaborate across teams to incorporate feedback and solve challenges.
• Learn new technologies quickly and communicate status effectively.

Skills

Python

Scala

Spark

Pandas

NumPy

Scikit-learn

Machine Learning

Research

Education

PhD in Computer Science or ML

Job description

Stripe, Inc. is offering PhD machine learning engineering internships for the summer of 2027. This is a unique chance to contribute to critical projects that enhance Stripe's products, including foundation models used for fraud detection, support, and predicting user behavior.

You will tackle challenging problems at the intersection of finance, technology, and data, working on projects like the Stripe Assistant and the Stripe Foundation Model, with collaboration across teams.