Stripe Logo

Stripe

PhD Machine Learning Engineer, New Grad

Reposted 22 Days Ago
San Francisco, CA
Entry level
San Francisco, CA
Entry level
Develop and deploy large-scale machine learning systems at Stripe, focusing on enhancing products through machine learning techniques and collaborating with teams.
The summary above was generated by AI
Who we areAbout Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career..

About the team

Stripe's Applied ML organization is excited to offer new grad PhD machine learning engineering positions for 2025. This is an exceptional opportunity to contribute to critical projects that directly enhance Stripe's suite of products, focusing on areas such as foundation models used for dozens of tasks e.g. fraud detection, enhanced support, and predicting user behavior.

You will tackle challenging problems at the intersection of finance, technology, and data. You'll have the chance to work on creative projects like the Stripe Assistant and the Stripe Foundation Model, which leverage machine learning to revolutionize how businesses interact with financial services and data.

What you’ll doResponsibilities
  • 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.
Who you areMinimum requirements
  • 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 2024 or spring/summer 2025.
  • 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.
Preferred qualifications
  • Two years of university education or equivalent experience, with in-depth knowledge in specific domains of machine learning.
  • 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.
Application requirements

Please submit the following with your application:

  • A description of your work history (either a resume, LinkedIn Profile, website, or other portfolio of work)
  • Examples of relevant work and your approach to learning, such as GitHub repositories, StackOverflow contributions, or other project portfolios.

Top Skills

Numpy
Pandas
Python
Scala
Scikit-Learn
Spark

Stripe San Francisco, California, USA Office

510 Townsend St, San Francisco, CA, United States, 94103

Similar Jobs

21 Days Ago
Hybrid
San Mateo, CA, USA
193K-255K Annually
Expert/Leader
193K-255K Annually
Expert/Leader
Computer Vision • Gaming • Software • Virtual Reality • Web3 • Metaverse
The Senior Machine Learning Engineer will develop end-to-end ML solutions for search, recommendation, and content understanding, focusing on deep learning and scalable production systems.
Top Skills: C#C++GoJavaLuaNode.jsPythonRubySwift
21 Days Ago
Hybrid
San Mateo, CA, USA
193K-255K Annually
Expert/Leader
193K-255K Annually
Expert/Leader
Computer Vision • Gaming • Software • Virtual Reality • Web3 • Metaverse
As a Senior Machine Learning Engineer, you'll build and implement advanced machine learning solutions, focusing on NLP, speech, and computer vision, while guiding technical direction and collaborating with various teams.
Top Skills: C#PythonSQL
21 Days Ago
Hybrid
San Mateo, CA, USA
193K-255K Annually
Expert/Leader
193K-255K Annually
Expert/Leader
Computer Vision • Gaming • Software • Virtual Reality • Web3 • Metaverse
The role involves developing advanced machine learning models for search and discovery, enhancing user engagement through end-to-end solutions in a large-scale environment.
Top Skills: C#C++GoPython

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account