Staff Machine Learning Engineer

Company Description

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

Job Description

About the team

The Security and Risk Engineering organization builds scalable, AI-powered security solutions that reduce risk and protect ServiceNow and its customers. We value AI-first thinking, clean architecture, intuitive experiences, and a culture of continuous learning.

This is a zero-to-one incubation. We’re building a new class of exposure analysis that ranks security work by exploitability—where an attacker could realistically get in—rather than raw severity. The architecture is evolving, and this role helps define what good looks like.

The role

As a Staff ML Engineer, you own a major subsystem of a novel exploitability engine end to end—for example the probability core, the exposure graph and entity-resolution layer, or the calibration and validation loop. You make the design calls within your area and drive them to production.

What you’ll own

• A major subsystem end-to-end—the probability core, the exposure graph and entity resolution, or the calibration and validation loop—including its design, delivery, and quality.
• The design decisions within your subsystem, and how it interfaces with the rest of the engine.
• The metrics that prove your subsystem works—entity-resolution accuracy, calibration quality, or path-ranking precision—o