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Coinbase

Machine Learning Engineer Intern

Hybrid - San Francisco, CAinternshipinternAdded 3 days ago

About this role

Coinbase is seeking a Machine Learning Engineer Intern for a 12-week summer 2027 internship to develop and deploy ML models and pipelines that enhance platform security, personalization, and blockchain applications. You'll lead an end-to-end research project applying modern ML techniques to real-world crypto problems while partnering with senior engineers and product teams.

What you'll do

  • Develop, deploy, and operate production-scale machine learning models and pipelines
  • Drive an end-to-end research project applying modern ML techniques to a defined business problem
  • Partner with senior engineers and product teams to identify new ML applications for blockchain and crypto use cases
  • Present findings and recommendations to cross-functional stakeholders at internship conclusion
  • Collaborate on ML applications that improve platform security and personalize user experiences

What they're looking for

  • PyTorch or TensorFlow
  • Supervised learning, unsupervised learning, or reinforcement learning
  • Python programming and production-quality code
  • Version control and software testing
  • Machine learning research and model training
  • Generative AI tools and responsible AI practices
  • Data handling for structured and unstructured datasets

Benefits

  • Work on high-impact ML projects at blockchain scale
  • Mentorship from senior ML engineers
  • Hybrid setup with quarterly in-person collaboration sessions
  • Exposure to cutting-edge ML techniques in crypto finance
  • Cross-functional partnership with product and engineering teams
Apply on the employer's site

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Coinbase

Coinbase builds cryptocurrency and financial services infrastructure, with a focus on internal platforms, developer tools, and compliance systems. The company is hiring software engineers, platform engineers, and analytics engineers to enhance developer infrastructure, support operations, power compliance workflows, and deliver data analytics solutions.

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Likely interview questions

  • Describe a research project you've worked on and how you took it from concept to implementation.
  • Walk us through your experience building and training models with PyTorch or TensorFlow.
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