Staff Machine Learning Engineer

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.

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—owned as first-class targets.
• Technical direction for the engineers working in your area.

What you’ll do

• Take a major, ambiguous subsystem from design through production at scale.
• Drive design and code reviews in your area, and raise the engineering bar around you.
• Mentor engineers and lead a workstream through influence.
• Partner with product, security R&D, and SecOps to turn customer problems into subsystem design.
• Establish AI safety, security, and guardrails for the agentic parts of your subsystem.

What you bring

• A track record of owning a significant system or subsystem end-to-end in production.
• Hands-on depth in agentic and LLM systems and/or probabilistic or ML-driven scoring—graph modeling, calibration, search and optimization.
• The primary skills required are Predictive Modeling, Graph ML, Security Analytics, Anomaly Detection, Risk Scoring, LLMs/Agentic AI, and MLOps, which align with advanced machine learning and AI engineering rather than traditional software development.
• Proven delivery of an ambiguous problem to a reliable production system that others depend on.
• The judgment to make sound design decisions under uncertainty within your area.
• Command of distributed systems, APIs, cloud-native development, and data or graph systems.
• Expert-level Python, and/or Java, Go, or TypeScript.
• Technical leadership that moves a workstream through influence.
• Applied interest in security problems—attack-path analysis, vulnerability management, identity security, threat intelligence, or detection and response—is preferred.
• Experience with AI-assisted development tools and coding agents such as Claude Code, Codex, Cursor, or Windsurf is a plus.
• Experience with AI evaluation, safety, governance, or policy guardrails is a plus.

• 6+ years of software engineering experience, including leading the design and delivery of complex production components.
• The primary skills required are Predictive Modeling, Graph ML, Security Analytics, Anomaly Detection, Risk Scoring, LLMs/Agentic AI, and MLOps. These skills align more closely with advanced machine learning and AI engineering than with traditional software development.
• Demonstrated experience as the technical owner or lead for a significant system or subsystem.
• Depth building AI/ML-powered production systems; probabilistic modeling, graph analytics, or calibration and evaluation is a strong plus.
• Modern AI experience: RAG, embeddings, vector search, agentic workflows, model evaluation, or AI observability.
• Strong programming experience in Python and/or Java, Go, or a similar language.
• Cloud-native technologies, distributed systems, APIs, databases, and scalable architectures.
• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience.
• Cybersecurity or security-product experience, or familiarity with modern security architectures and operations, is strongly preferred.

For positions in this location, we offer a base pay of $176,100 - $308,200, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. 

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.

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