Machine Learning Engineer Intern

<div class="content-intro"><p>Ready to do the most impactful work of your career? At&nbsp;<a href="https://www.coinbase.com/?utm_campaign=mt_o_m_w_m_m__coi_0_jd-onchain&amp;utm_source=coinbase">Coinbase</a>, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”&nbsp;<a href="https://www.coinbase.com/careers">learn more about working at Coinbase</a>.</p></div><p>This is a 12-week internship during summer 2027.&nbsp;</p> <p>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.</p> <p><strong>What you'll do:</strong></p> <ul> <li>Develop, deploy, and operate machine learning models and pipelines at production scale</li> <li>Drive an end-to-end research project applying modern ML techniques to solve a defined business problem</li> <li>Partner with senior engineers and product teams to identify new ML applications for blockchain and crypto use cases</li> <li>Present findings and recommendations to cross-functional stakeholders at the conclusion of your internship</li> </ul> <p><strong>Required Skills and Experience:</strong></p> <ul> <li>Currently pursuing a Ph.D. with published or in-progress research in machine learning, deep learning, or a closely related field</li> <li>Demonstrated proficiency building and training models using ML frameworks such as PyTorch or TensorFlow</li> <li>Experience applying ML techniques including supervised learning, unsupervised learning, or reinforcement learning to structured or unstructured datasets</li> <li>Familiarity with software engineering fundamentals including version control, testing, and writing production-quality Python code</li> <li>Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.</li> </ul> <p>&nbsp;</p> <p>Req ID: P78143</p> <p>#LI-Hybrid</p> <div id="fortidlp-i