Employer listing
Machine Learning Engineer Intern
Coinbase
San Francisco, Ca · hybrid · internship · Intern
Salary not specified
Role
Join Coinbase's Machine Learning team for a 12-week internship during summer 2027. Work alongside senior engineers on ML models and pipelines that improve platform security, personalize user experiences, and enable new crypto use cases. Own a research-to-production project applying modern ML techniques to real-world problems at blockchain scale.
The position is hybrid in San Francisco, CA. Coinbase is remote-first, not remote-only, with quarterly in-person working sessions called “surges.”
Responsibilities
- Develop, deploy, and operate machine learning models and pipelines at production scale.
- 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 ML applications for blockchain and crypto use cases.
- Present findings and recommendations to cross-functional stakeholders at the conclusion of the internship.
Required Qualifications
- 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 supervised learning, unsupervised learning, or reinforcement learning to structured or unstructured datasets.
- Familiarity with software engineering fundamentals, including version control, testing, and production-quality Python code.
- Responsible use of generative AI, maintaining human oversight to deliver business-ready outputs and measurable improvements in workflow efficiency, cost, and quality.
Compensation
- Target hourly rate: $60 USD.
Application Information
- Requisition ID: P78143.
- Candidates may submit a maximum of three applications within a six-month period.
- Applicants needing reasonable accommodations may email their request and contact information to accommodations@coinbase.com.
- Submitting an application indicates agreement to the Candidate Privacy Notice. US applicants also agree to Arbitration of Disputes.