PhD, Machine Learning Engineering Intern


San Francisco, CA, USA


Sep 29

This job is no longer accepting applications.

Tackle difficult problems with rewarding solutions at Stripe 

Our internship program will provide an opportunity to work on meaningful products that will grow the GDP of the internet. Through the internship, you will work with many systems and technologies, gain experience in systems design, testing, and opportunities to talk about your work to the broader company. Each intern has a dedicated mentor, and every project is part of the team’s roadmap and will directly help Stripe’s mission. Some recent projects have been rebuilding our statistics aggregation service, building new service discovery systems, and many user facing projects like making it easy to understand error messages on Stripe Checkout. As a Stripe intern, you won’t just be working on important projects to increase global commerce, you’ll work alongside exceptional people who insist on doing their best work. You’ll work and learn from people with high standards who are great at inspiring others to do more and go further. We value technical and personal growth, and see our internship program as a vehicle to foster both.

Stripe’s Merchant Intelligence organization is looking for PhD machine learning engineering interns to work across our identity, radar, credit, supportability, and fraud teams.

You will:

  • Build large-scale cutting-edge Machine Learning systems that have outsized business impact
  • Have a hand in mission-critical work of building and deploying the models that help Stripe enable access to economic infrastructure for a huge variety of businesses across the globe
  • Design, train, improve & launch models
  • Write software that will be used in production, and has meaningful impact to Stripe
  • Give and receive technical feedback through code reviews or design discussions
  • Collaborate with other engineers (and people from other disciplines) to proactively seek and incorporate feedback
  • Learn quickly by asking great questions, finding how to work with your mentor and teammates effectively, and communicate the status of your work clearly

We’re looking for someone with:

  • A strong fundamental understanding of Computer Science through pursuit of a PhD degree in Computer Science, Machine Learning, or a related discipline
  • Some programming experience and familiarity, either through side projects or classwork. We work mostly in Ruby, JavaScript, Scala, and Go. We believe new programming languages can be learned if the fundamentals and general knowledge is present
  • Machine Learning expertise in supervised learning (deep & wide networks, sequential models, Natural Language Processing, etc.), unsupervised learning (anomaly detection, reinforcement learning, clustering, etc.) and/or ML Operations (interpretability, debugging, calibration, etc.)
  • Experience from previous internships or other multi-person projects, including open source contributions, that demonstrate evaluating and receiving feedback from mentors, peers, and stakeholders
  • Ability to learn unfamiliar systems and form an understanding of those systems, through independent research and working with a mentor and subject matter experts

You also likely have:

  • 2 years of university education, or equivalent work experience
  • A couple areas of more in-depth domain-knowledge or focus, as well as general skills and knowledge, in machine learning systems and libraries
  • Understanding and some experience writing high quality pull requests, with good test coverage, and working knowledge to complete projects with minimal defects
  • Familiarity with navigating and managing your work in new code bases, with multiple languages
  • Ability to write clearly to explain your work to stakeholders, team members, and other Stripes

Please include these in your application: 

  • A description of your work history (either a resume, LinkedIn Profile, website, or other portfolio of work)
  • Examples of your relevant work and approach to learning (GitHub, StackOverflow, other projects including open source contributions)
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