Coinbase is seeking a Machine Learning Engineer to join their Risk AI/ML team to build sophisticated models that protect customers from fraud, account takeovers, and scams, thereby making Coinbase the most trusted platform in crypto and enabling future products.
Requirements
- 4+ years of professional experience in software engineering and/or AI/ML, with experience deploying AI/ML systems into production.
- Familiarity with applied AI/ML techniques (e.g., Risk ML, deep learning, NLP, recommender systems, anomaly detection).
- Proficient coding skills (e.g., Python) with experience in AI/ML frameworks (TensorFlow, PyTorch).
- 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.
Responsibilities
- Use our centralized, self-service ML platform to own the end-to-end development of ML models, from ideation to production.
- Enhance our core models, including the Scam Models, Transfer/Transaction Risk Models, Withdrawal Limit Models, and Account Takeover models.
- Act on new threat data to build, train, and deploy permanent ML models that replace temporary rules—targeting a deploy-to-production timeline of under one week.
- 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 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.
- 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.
- Work closely with stakeholders from Risk Operations, Platform Engineering, and Product Management to close the feedback loop, turning new threats into automated defenses.
Other
- A commitment to building an open financial system and a strong desire to protect users from fraud and scams.
- Embody core cultural values: add positive energy, communicate clearly, be curious, and be a builder.
- Ability to work collaboratively on technical initiatives and contribute to impactful AI/ML solutions.
- Strong communication skills, with the ability to convey technical concepts to both technical and non-technical audiences.
- In-person participation is required throughout the year. Team and company-wide offsites are held multiple times annually to foster collaboration, connection, and alignment. Attendance is expected and fully supported.
