
PhD Machine Learning Engineer, Intern
- USA
- $123,500-161,525 per year
- Training
- Full-time
- Develop and deploy large-scale machine learning systems that drive significant business value across various domains.
- Engage in the end-to-end process of designing, training, improving, and launching machine learning models.
- Write production-scale ML models that will be deployed to help Stripe enable economic infrastructure access for a diverse range of businesses globally.
- Collaborate across teams to incorporate feedback and proactively seek solutions to challenges.
- Rapidly learn new technologies and approaches, demonstrating a strong ability to ask insightful questions and communicate the status of your work effectively.
- A deep understanding of computer science, obtained through the pursuit of a PhD in Computer Science, Machine Learning, or a closely related field, with the expectation of graduating in winter 2026 or spring/summer 2027.
- Practical experience with programming and machine learning, evidenced by projects, classwork, or research. Familiarity with languages such as Python, Scala, Spark and libraries such as Pandas, NumPy, and Scikit-learn.
- Expertise in areas of machine learning such as supervised and unsupervised learning techniques, ML operations, and possibly experience in Large Language Models or Reinforcement Learning.
- Demonstrated ability to work on collaborative projects, with experience in receiving and applying feedback from various stakeholders.
- A proactive approach to learning unfamiliar systems and a demonstrated ability to understand complex systems independently.
- Intent to return to the degree-program after the completion of the internship/co-op.
- Two years of university education or equivalent experience, with in-depth knowledge in specific domains of machine learning.
- Published and presented peer-reviewed articles in top-tier venues.
- Experience in writing high-quality pull requests, maintaining good test coverage, and completing projects with minimal defects.
- Familiarity with navigating new codebases and managing work across different programming languages.
- Excellent written communication skills to clearly articulate your work to both team members and wider Stripe audiences.
- A detailed resume or LinkedIn profile showcasing your work history.
- Examples of relevant work and your approach to learning, such as GitHub repositories, StackOverflow contributions, or other project portfolios.