Role Description & Responsibilities
Machine Learning
About Coinbase
Coinbase is a high-growth technology leader building scalable solutions for global users. Millions of companies and teams rely on their infrastructure and services to execute high-value workflows, analyze massive datasets, and scale modern operations.
CadetX Candidate Advantage: As an applicant for this Machine Learning role, you are evaluated on practical proficiency with real-world query execution, data pipelines, and clear stakeholder communication.
CadetX Role Brief & Company Specifications
Role Mission & Impact
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.
Key Responsibilities & Day-to-Day Scope
- ✓ Develop, deploy, and operate machine learning models and pipelines at production scale
- ✓ Drive an end-to-end research project applying modern ML techniques to solve 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 conclusion of your internship
- ✓ Currently pursuing a Ph.D. with published or in-progress research in machine learning, deep learning, or a closely related field
Official Qualifications & Technical Requirements
- • Demonstrated proficiency building and training models using ML frameworks such as PyTorch or TensorFlow
- • Experience applying ML techniques including supervised learning, unsupervised learning, or reinforcement learning to structured or unstructured datasets
- • Familiarity with software engineering fundamentals including version control, testing, and writing production-quality Python code
- • Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.
Preferred Skills & Technology Stack
- + Familiarity with MLOps pipelines (Docker, Kubernetes, Kubeflow, Triton Inference Server).
- + Knowledge of distributed training techniques and GPU acceleration (CUDA).
- + Relevant coursework, research publication, or open-source contribution in ML/DL.
Tech Stack & Tools in this role
Expected technical competencies for Day 1 productivity:
★ Life & Culture at Coinbase
Verified EmployerCoinbase champions rigorous analytical discipline, continuous learning, and low-ego teamwork. Team members enjoy flexible hybrid allowances, learning stipends, and structured mentorship to fast-track career mobility.