Senior ML Engineer: AI Copilot & Multi-Agent Systems

Showcify, Inc.; United States; Remote; USD 191,000 - 225,000; Full time

Job summary

Coinbase is seeking a Senior Machine Learning Engineer on the CX Intelligence Engineering team within Coinbase's Customer Engagement and Experience org. You’ll design and build AI-powered systems that connect our Help Center, chatbots, and agent workflows.

This role requires 5+ years of ML and software engineering experience, deep knowledge of LLMs and AI ecosystems, and a focus on responsible AI with human oversight to drive efficient, scalable customer outcomes.

Qualifications

• 5+ years of professional experience in ML and software engineering.
• Hands-on expertise with large language models and generative AI ecosystems.
• Proficiency in Python for production ML code.
• Specialized depth in NLP, information retrieval, conversational AI, or statistical modeling.
• Ability to write technical design docs and communicate ML concepts clearly.
• Responsible use of generative AI with human oversight.
• Experience using AI copilots/tools (e.g., LangGraph, LangSmith, Vertex AI, AWS Bedrock).

Responsibilities

• Architect and deploy the multi-agent framework for agent assist and secure LLM-powered actions.
• Own end-to-end project execution for complex ML initiatives.
• Build and optimize AI-driven concierge chat and agent copilot experiences.
• Develop systems to detect bad actors and ensure safety at scale.
• Establish best practices for ML system design and mentor team members.

Skills

Python

LLMs / NLP

Production ML at scale

Cross-functional communication

Project ownership

Tools

LangGraph

LangSmith

Vertex AI

AWS Bedrock

LibreChat

Gemini

Glean

Job description

Coinbase is seeking a Senior Machine Learning Engineer on the CX Intelligence Engineering team within Coinbase's Customer Engagement and Experience org. You’ll design and build AI-powered systems that connect our Help Center, chatbots, and agent workflows.

This role requires 5+ years of ML and software engineering experience, deep knowledge of LLMs and AI ecosystems, and a focus on responsible AI with human oversight to drive efficient, scalable customer outcomes.