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))
Principal Machine Learning Engineer leading AI and Machine Learning systems at Bumble for recommendations and personalization. Driving improvements in user engagement and safety across Bumble products.
Software Engineer delivering MLOps solutions for Generative AI at DataGalaxy. Focusing on reliability and collaboration with product engineering teams in a hybrid environment.
Senior Machine Learning Engineer responsible for designing, building, and deploying ML solutions. Joining a global tech group tackling high - impact projects in Buenos Aires.
Principal Machine Learning Engineer at Qodea responsible for leading ML model lifecycle and collaborating on AI solutions in Buenos Aires delivery center.
Lead ML Ops Engineer for a fast - growing AI startup focused on scalable infrastructure. Drive hands - on execution across the entire model lifecycle in a collaborative environment.
Lead Machine Learning Engineer creating personalized item recommendations for Target.com and the Target App. Designing and optimizing production ML solutions with a team of data scientists and engineers.
Senior Machine Learning Engineer at Doctrine focusing on developing NLP models for legal document processing. Join an ambitious team to innovate within the field of legal technology.
Senior ML Engineer developing scalable production ML systems across various teams in JobCloud. Leading innovation in the AI - driven recruitment landscape, improving job ad visibility and performance.
MLOps Engineer responsible for designing and maintaining ML pipelines at JobCloud. Collaborating with teams to productionize ML models and ensuring robust system performance.
Senior Machine Learning Engineer at greehill developing ML solutions for sustainable urban living. Leading projects in Computer Vision and Deep Learning to transform urban environments.