Staff Machine Learning Engineer, Compliance Automation (Platform)

Coinbase

10h•$218,025 - $256,500•Remote

About The Position

As a Staff Machine Learning Engineer on Coinbase’s Compliance Automation team within the Platform group, you will build AI systems that automate compliance operations at scale. The team develops and ships Agentic AI solutions for processes including investigations and decision support, replacing manual work with intelligent, auditable, and measurable automation. You will own the machine-learning architecture for production compliance agents and make technical decisions about model selection, grounding, guardrails, and evaluation, while working with Compliance stakeholders to ensure automated outputs meet regulatory standards. Coinbase is remote-first but not remote-only. Employees are expected to gather quarterly for in-person working sessions called “surges.” The position’s annual base salary range is $218,025–$256,500 USD, excluding equity and bonus. Total compensation may also include equity, bonus eligibility, and medical, dental, vision, and 401(k) benefits.

Requirements

At least 8 years of experience in machine learning and software engineering.
Demonstrated experience shipping LLM-based or Agentic AI applications to production.
Deep expertise in LLM application development, including prompt engineering, retrieval-augmented generation (RAG), grounding techniques, hallucination reduction, and agent orchestration frameworks.
Track record building production ML evaluation and measurement systems, including monitoring for drift, accuracy degradation, and output quality at scale.
Strong Python proficiency and hands-on experience with generative AI frameworks and ML infrastructure, such as LangChain, vector databases, Airflow, Spark, or equivalent orchestration and data-processing tools.
Experience in compliance, regulatory technology, financial crimes, or a similarly regulated domain where auditability, explainability, and correctness of automated decisions are critical.
Use generative AI responsibly, maintaining human oversight to deliver business-ready outputs and measurable improvements in workflow efficiency, cost, and quality.

Responsibilities

Architect and build production Agentic AI systems for compliance automation, including LLM-powered agents, orchestration pipelines, and decision-support workflows.
Own the ML technical direction for compliance agents, including model selection, prompt engineering, grounding strategies, and guardrail design.
Design and implement evaluation and measurement frameworks to quantify agent performance, detect hallucinations and drift, and provide auditability for compliance teams and regulators.
Partner with Compliance, Legal, and Operations stakeholders to turn regulatory workflows into technical specifications and identify processes suited to full automation or human-in-the-loop augmentation.
Mentor engineers on ML system design, LLM application patterns, and responsible AI practices.