Machine Learning Engineer, Risk AI/ML

Position Overview

At Coinbase, our mission is to increase economic freedom in the world by leveraging crypto and blockchain technology. As a Machine Learning Engineer on the Risk AI/ML team, you will design, deploy, and iterate on sophisticated models that prevent fraud, account takeovers, and scams—all while building the future global financial system. This hands‑on, in‑person role demands high-caliber collaboration, rapid execution, and a passion for tackling the company’s toughest challenges. Job ID: GPML04US

Key Responsibilities

• Focus on Modeling: Leverage Coinbase’s self‑service ML platform to own end‑to‑end development of ML models from ideation to production.
• Improve Core Model Performance: Enhance core models—including Scam Models, Transfer/Transaction Risk Models, Withdrawal Limit Models, and Account Takeover models.
• Rapidly Respond to Threats: Build, train, and deploy permanent ML models (targeting a deploy-to-production timeline under one week) based on new threat data.
• Build & Deploy Scalable Models: Develop production‑grade AI/ML models and pipelines, utilizing automated CI/CD processes and a centralized feature store.
• Apply Advanced ML Techniques: Employ methodologies such as deep learning, NLP, Graph Neural Networks, sequence modeling, and LLMs to tackle complex, crypto‑native challenges.
• Build Context-Aware Risk Systems: Develop adaptive logic that determines appropriate friction (e.g., quizzes, LLM agents, human reviews) for different user segments.
• Collaborate and Execute: Work closely with Risk Operations, Platform Engineering, and Product Management to convert threat insights into automated defenses.

Required Qualifications

• 4+ years of professional experience in software engineering and/or AI/ML, with deployment of systems into production.
• Passion & Values: A commitment to building an open financial system and protecting users from fraud and scams, while embodying Coinbase’s core cultural values.
• AI/ML Knowledge: Familiarity with applied AI/ML techniques including risk modeling, deep learning, NLP, and anomaly detection.
• Technical & Coding Skills: Proficiency in Python and experience with AI/ML frameworks (e.g., TensorFlow, PyTorch); backend systems experience is a plus.
• Team Collaboration: Proven ability to work collaboratively on technical initiatives.
• Communication Skills: Strong capability to explain technical concepts to both technical and non-technical audiences.

Preferred Qualifications

• 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, Model Serving solutions, Apache Airflow, Spark, Kafka).
• Experience with Graph Neural Networks, Sequential Models (like LSTMs), LLMs, or Reinforcement Learning.
• Understanding of MLOps best practices, including monitoring and iterative improvement of production models.
• Experience with data analysis and visualization tools.

Benefits & Perks

• Compensation: Target annual salary of $152,405–$179,300 USD (range may vary based on location).
• Bonus eligibility: Qualify for annual bonuses as part of full‑time offers.
• Equity eligibility: Opportunity to receive equity as part of your compensation package.
• Benefits: Comprehensive benefits including medical, dental, vision, and 401(k).