Coinbase
FinTech
SeniorMachineLearningEngineer,CXIntelligence
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Machine Learning Engineer, CX Intelligence at Coinbase. Skills: Machine Learning, Distributed Systems. Design and build machine learning systems. Build and maintain production ML systems”
Industry & Context.
What They're Looking For.
Must Have
5+ years of experience in software engineering, Experience with large-scale distributed systems, Experience with machine learning systems, Experience with Python
Nice to Have
Experience with C++, Experience with distributed systems, Experience with machine learning systems, Experience with Python
What You'll Do.
Design and build machine learning systems
Build and maintain production ML systems
Develop and deploy ML models
Collaborate with product and engineering teams
Improve ML system performance
Ensure ML system reliability
How You'll Work.
Team & Collaboration
Product and engineering teams
Full Job Description
Ready to do the most impactful work of your career? At Coinbase, we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase. As a Machine Learning Engineer on the CX Intelligence team within Enterprise Applications and Architecture, you'll build the AI-powered conversational systems that connect Coinbase's Help Center, chatbots, and agent workflows. The team owns the multi-agent platform powering Coinbase Chat and agent tooling, partnering with Conversation Design, CX, and Engineering to deliver secure, scalable automated support. You'll lead the design and implementation of a unified orchestration layer that coordinates interactions between vendor AI, internal multi-agent systems, and human participants, directly improving how millions of customers get help. What you'll do: Architect and deploy the orchestration layer that manages state transitions, context sharing, and intent routing across vendor and internal LLM frameworks in a distributed conversational environment. Build production-grade Python services that bridge advanced ML/AI research with reliable, measurable customer-facing products. Lead end-to-end project execution for complex ML initiatives, managing priorities, technical trade-offs, and cross-functional dependencies from design through delivery. Establish best practices for system design, coding standards, and AI/ML development workflows across the team. Mentor engineers on architectural integrity and modern AI/ML patterns, raising the technical bar for the broader team. Conduct design r
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