Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 3
Blockchain
Deep Learning
GenAI
Generative AI @ 3
Machine Learning @ 3
PyTorch @ 5
Python @ 2
Reinforcement Learning @ 3
TensorFlow @ 5
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Coinbase is a remote-first, but not remote-only company, with quarterly in-person working sessions called “surges.” This is a 12-week internship during summer 2027. You will join Coinbase’s Machine Learning team and work alongside senior engineers building machine learning models and pipelines that make the platform more secure, personalize user experiences, and unlock new use cases for crypto. As a Machine Learning Engineer Intern, you will take ownership of a research-to-production project, applying modern machine learning techniques to real-world problems at blockchain scale.
Responsibilities
- Develop, deploy, and operate machine learning models and pipelines at production scale.
- Drive an end-to-end research project applying modern machine learning techniques to solve a defined business problem.
- Partner with senior engineers and product teams to identify new machine learning applications for blockchain and crypto use cases.
- Present findings and recommendations to cross-functional stakeholders at the conclusion of the internship.
Requirements
- 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 machine learning frameworks such as PyTorch or TensorFlow.
- Experience applying supervised learning, unsupervised learning, or reinforcement learning techniques to structured or unstructured datasets.
- Familiarity with software engineering fundamentals, including version control, testing, and writing production-quality Python code.
- Responsible use of generative AI, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
Additional Information
- Candidates may submit a maximum of three applications within a six-month period.
- Req ID: P78143.
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