Remote ML Engineer Intern: Production-Scale Models

FDE Times; San Francisco (CA); Hybrid; USD 68,000 - 97,000; Part time

Benefits offered by this job

In-person surge sessions

Job summary

Coinbase is offering a 12-week ML internship in San Francisco, combining production-scale model work with research. You will join the Machine Learning team to build, deploy, and optimize models that enhance security, user experience, and new crypto use cases. This remote-first program includes quarterly in-person surge sessions.

You will work with senior engineers and product teams, conducting an end-to-end research project and presenting findings to stakeholders at the internship's conclusion.

Qualifications

• PhD candidate in ML with published or in-progress research.
• Proficiency building and training models using ML frameworks (PyTorch, TensorFlow).
• Experience applying ML techniques (supervised/unsupervised/reinforcement learning) to varied data.
• Familiarity with software engineering fundamentals (version control, testing, production-quality Python).
• Responsible use of Generative AI to deliver business-ready outputs and improve workflow efficiency.

Responsibilities

• Develop, deploy, and operate ML 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 new ML applications for blockchain and crypto use cases.
• Present findings and recommendations to cross-functional stakeholders at the end of the internship.

Skills

Python

PyTorch

ML research

Production code

TensorFlow

Education

PhD in ML/DL

Job description

Coinbase is offering a 12-week ML internship in San Francisco, combining production-scale model work with research. You will join the Machine Learning team to build, deploy, and optimize models that enhance security, user experience, and new crypto use cases. This remote-first program includes quarterly in-person surge sessions.

You will work with senior engineers and product teams, conducting an end-to-end research project and presenting findings to stakeholders at the internship's conclusion.