Senior ML Engineer — AI Concierge & Multi-Agent Systems

Coinbase, Inc.; New York (NY); Hybrid; USD 191,000 - 225,000; Full time

Benefits offered by this job

Equity

Bonus eligibility

Medical benefits

Dental benefits

Vision benefits

401(k)

Job summary

Coinbase is seeking a Senior Machine Learning Engineer to join the CX Intelligence Engineering team. You will design AI-powered systems that connect Help Center, chatbots, and agent workflows, delivering secure, scalable AI support across customer experiences.

You will lead end-to-end ML initiatives, build agent co-pilot experiences, and drive automation that speeds resolutions while maintaining safety and compliance. A remote-first, hybrid work model supports quarterly in-person surges.

Qualifications

• 5+ years in machine learning and software engineering with production ML experience.
• Hands-on with large language models and generative AI ecosystems.
• Proficiency in Python for production ML applications.
• Specialized depth in NLP, information retrieval, or conversational AI.

Responsibilities

• Architect and deploy a multi-agent framework for agent assist and secure LLM actions.
• Own end-to-end ML initiatives, managing priorities and trade-offs.
• Build AI-driven concierge chat and agent copilot experiences to improve resolution rates.
• Develop systems to detect bad actors and ensure platform safety at scale.
• Set best practices for design, coding and evaluation in ML/AI systems.

Skills

Python

LLMs

Deep learning

Generative AI

Production ML

NLP

Information retrieval

Conversational AI

Tools

LangGraph

LangSmith

Google ADK

Vertex AI

AWS Bedrock

Job description

Coinbase is seeking a Senior Machine Learning Engineer to join the CX Intelligence Engineering team. You will design AI-powered systems that connect Help Center, chatbots, and agent workflows, delivering secure, scalable AI support across customer experiences.

You will lead end-to-end ML initiatives, build agent co-pilot experiences, and drive automation that speeds resolutions while maintaining safety and compliance. A remote-first, hybrid work model supports quarterly in-person surges.