Coinbase Machine Learning Engineer Intern Summer 2027 San Francisco
Apply by 22 Dec 2026
Key Facts
| Role | Machine Learning Engineer Intern |
|---|---|
| Company | Coinbase |
| Location(s) | Hybrid — San Francisco, CA |
| Term | Summer 2027 (12 weeks) |
| Deadline | Rolling — no firm deadline listed (apply early) |
| Pay / stipend | See official posting |
Overview
Coinbase’s Machine Learning team builds models and pipelines that harden the platform, personalize experiences, and open new crypto use cases. The 12-week Summer 2027 MLE internship is research-to-production: develop and operate models at scale, partner with senior engineers and product, and present findings at the end.
Hybrid San Francisco with quarterly “surges.” Best fit for Ph.D. candidates with published or in-progress ML research and strong PyTorch/TensorFlow chops.
Eligibility / Key Requirements
- Currently pursuing a Ph.D. with published or in-progress ML / deep learning research
- Proficiency building/training models in PyTorch or TensorFlow
- Experience with supervised, unsupervised, or reinforcement learning
- Software engineering fundamentals: Git, testing, production-quality Python
- Available for a 12-week Summer 2027 internship (hybrid SF)
How to Apply
- Open the official application from EduBard’s Apply button for this role.
- Create or sign in to your employer careers account.
- Submit your resume and any required materials before the deadline.
Compiled from the official posting; verify details on the employer site before applying.