Machine Learning Engineer focused on building sophisticated models to protect Coinbase users from fraud. Engaging in hands-on technical role with modern AI/ML methodologies.
Responsibilities
Use our centralized, self-service ML platform to own the end-to-end development of ML models, from ideation to production.
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.
Act on new threat data (identified by our Risk Operations partners) to build, train, and deploy permanent ML models.
Develop production-grade AI/ML models and pipelines that enable reliable, real-time predictions.
Apply modern methodologies (e.g., deep learning, NLP, Graph Neural Networks (GNNs), sequence modeling, and LLMs for NLP and conversational agents) to solve complex challenges.
Go beyond a single score to help build adaptive logic for user evaluation based on risk.
Work closely with stakeholders to close feedback loops and implement automated defenses.
Requirements
4+ years of professional experience in software engineering and/or AI/ML, with experience deploying AI/ML systems into production.
A commitment to building an open financial system and a strong desire to protect users from fraud and scams.
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).
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.
Benefits
bonus eligibility
equity eligibility
benefits (including medical, dental, vision and 401(k))
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