About this opportunity
CryptoproNetwork lists this Machine Learning Engineer Intern opportunity in san francisco, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
This is a 12-week internship during summer 2027.
You'll join Coinbase's Machine Learning team and work alongside senior engineers building ML models and pipelines that make our platform more secure, personalize user experiences, and unlock new use cases for crypto. As an MLE intern, you'll take ownership of a research-to-production project, applying cutting-edge ML techniques to real-world problems at blockchain scale.
What you'll do:
Develop, deploy, and operate machine learning models and pipelines at production scale
Drive an end-to-end research project applying modern ML techniques to solve 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 the conclusion of your internship
Required Skills and Experience:
Currently pursuing a Ph.D. with published or in-progress research in machine learning, deep learning, or a closely related field
Demonstrated proficiency building and training models using ML frameworks such as PyTorch or TensorFlow
Experience applying ML techniques including supervised learning, unsupervised learning, or reinforcement learning to structured or unstructured datasets
Familiarity with software engineering fundamentals including version control, testing, and writing production-quality Python code
Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
Pay Transparency Notice:Depending on your work location, the target hourly rate for this position can range as detailed below.Hourly Rate:$60—$60 USD
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Worksite address
san francisco, CA, 94199, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.