Who you are

• 4+ years of professional experience in software engineering and/or AI/ML, with experience deploying AI/ML systems into production
• Passion & Values: A commitment to building an open financial system and a strong desire to protect users from fraud and scams. You embody our core cultural values: add positive energy, communicate clearly, be curious, and be a builder
• AI/ML Knowledge: Familiarity with applied AI/ML techniques (e.g., Risk ML, deep learning, NLP, recommender systems, anomaly detection)
• Technical & Coding Skills: Proficient coding skills (e.g., Python) with experience in AI/ML frameworks (TensorFlow, PyTorch). Experience in building backend systems with a focus on data processing or analytics is a plus
• Team Collaboration: Ability to work collaboratively on technical initiatives and contribute to impactful AI/ML solutions
• Communication Skills: Strong communication skills, with the ability to convey technical concepts to both technical and non-technical audiences
• Bachelor’s degree in Computer Science, AI/ML, Data Science, or a related field
• Familiarity with modern data and AI/ML infrastructure (e.g., Feature Stores like Tecton, Model Serving like RayServe, Apache Airflow, Spark, Kafka)
• Experience with Graph Neural Networks (GNNs) or Sequential Models (like LSTMs)
• Experience with LLMs (NLP, fine-tuning, agentic systems) or Reinforcement Learning
• Understanding of MLOps best practices, including monitoring and improving production models
• Experience with data analysis and visualization tools

What the job involves

• We are looking for a Machine Learning Engineer to join our Risk AI/ML team. We are dedicated to building the sophisticated models that protect our customers and make Coinbase the most trusted platform in crypto
• Your work will directly prevent fraud, account takeovers, and scams, while enabling future products like instant guest checkout and Coinbase Cards
• This is a hands-on technical role where you will leverage our cutting-edge, self-service ML platform to rapidly design, deploy, and iterate on the models that defend millions of users
• Focus on Modeling: Use our centralized, self-service ML platform to own the end-to-end development of ML models, from ideation to production
• Improve Core Model Performance: Join a high-priority "pod" to enhance our core models, including the Scam Models, Transfer/Transaction Risk Models, Withdrawal Limit Models, and Account Takeover models
• Rapidly Respond to Threats: Act on new threat data (identified by our Risk Operations partners) to build, train, and deploy permanent ML models that replace temporary rules—targeting a deploy-to-production timeline of under one week
• Build & Deploy Scalable Models: Develop production-grade AI/ML models and pipelines that enable reliable, real-time predictions, leveraging our platform's automated CI/CD pipelines and centralized feature store
• Apply Advanced ML: Apply modern methodologies (e.g., deep learning, NLP, Graph Neural Networks (GNNs), sequence modeling, and LLMs for NLP and conversational agents) to solve complex, crypto-native challenges—all while focusing 100% on modeling, not infrastructure plumbing
• Build Context-Aware Risk Systems: Go beyond a single score. You will help build the adaptive logic that decides which friction (a quiz, an LLM agent, a human review) to apply to which user (e.g., new user, high-value trader), balancing security with user experience
• Collaborate and Execute: Work closely with stakeholders from Risk Operations, Platform Engineering, and Product Management to close the feedback loop, turning new threats into automated defenses