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 Senior ML Engineer, you build core components of a novel exploitability engine—shipping production ML that turns raw security signal into ranked, reachable attack paths. You take well-scoped problems from design to production and grow into deeper ownership as the system matures.
What you’ll own
- Well-scoped components of the engine—evidence ingestion and connectors, entity resolution, graph construction, or parts of the probability core—built to production quality.
- The correctness and reliability of what you ship: tests, evaluation, observability, and the metrics that show your component works.
- Turning ambiguous requirements into working code, with guidance on the calls that shape the wider system.
- The data and model plumbing that keeps the graph accurate—entity-resolution quality, evidence provenance, and decay.
What you’ll do
- Design, build, test, and operate production ML components with strong engineering fundamentals.
- Contribute to design and code reviews, and help raise the quality bar on the team.
- Prototype quickly to evaluate new AI capabilities against real cybersecurity problems.
- Partner with product, security R&D, and SecOps to understand the problem behind the ticket.
- Apply AI safety, security, and guardrail practices to what you build.
What you bring
- Solid software engineering fundamentals and experience operating production-quality software.
- Hands-on experience building ML- or LLM-powered applications—RAG, embeddings, agents, or probabilistic or ML-driven scoring.
- Experience taking a prototype to a reliable, maintainable production solution.
- Working knowledge of distributed systems, APIs, cloud-native development, and data or graph systems.
- Strong Python, and/or Java, Go, or TypeScript.
- Interest in security problems—vulnerability management, identity security, threat detection, or risk prioritization.
- 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, or guardrails is a plus.
- 3+ years of software engineering experience, or equivalent practical experience.
- 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.
- Experience designing and delivering production software systems.
- Experience building or integrating AI/ML-powered applications in a production or near-production environment.
- Modern AI experience: LLMs, 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 is a plus.
For positions in this location, we offer a base pay of $143,200 - $243,400, 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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