Staff ML Engineer, Compliance Automation (Agentic AI)

Coinbase, Inc.; United States; Hybrid; USD 218,000 - 257,000; Full time

Job summary

Coinbase, Inc. is seeking a Staff Machine Learning Engineer for the Compliance Automation team. You will own the ML architecture for production compliance agents, building Agentic AI solutions that automate investigations, decision support, and related workflows.

You will partner with Compliance to ensure outputs meet regulatory standards and mentor engineers on responsible AI practices. The role emphasizes leadership in ML system design, prompt engineering, and governance, with a focus on

Qualifications

• 8+ years in machine learning and software engineering.
• Shipping LLM-based or Agentic AI applications to production.
• Experience in compliance, regulatory tech, or regulated domains.
• Strong Python proficiency with GenAI frameworks.
• Experience building evaluation/monitoring for ML models.

Responsibilities

• Architect and build production Agentic AI systems for compliance automation, incl. LLM-powered agents and orchestration pipelines.
• Own ML technical direction for compliance agents, incl. model selection, prompt engineering, grounding and guardrails.
• Design and implement evaluation frameworks to quantify agent performance and detect drift and hallucinations.
• Partner with Compliance, Legal and Operations to translate regulatory workflows into automatable specs.
• Mentor engineers on ML system design and responsible AI practices.

Skills

LLM apps

Prompt engineering

RAG

Agentic AI

Model evaluation

Python

GenAI frameworks

Tools

LangChain

Vector databases

Airflow

Spark

Job description

Coinbase, Inc. is seeking a Staff Machine Learning Engineer for the Compliance Automation team. You will own the ML architecture for production compliance agents, building Agentic AI solutions that automate investigations, decision support, and related workflows.

You will partner with Compliance to ensure outputs meet regulatory standards and mentor engineers on responsible AI practices. The role emphasizes leadership in ML system design, prompt engineering, and governance, with a focus on