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Salary: USD 176,100 - 308,200 / annual
ServiceNow's Security and Risk Engineering organization is building a new class of AI-powered exposure analysis that ranks security work by exploitability—where an attacker could realistically get in—rather than raw severity. This is a zero-to-one incubation with an evolving architecture.
As a Staff ML Engineer, you will own a major subsystem of a novel exploitability engine end-to-end. This could be the probability core, the exposure graph and entity-resolution layer, or the calibration and validation loop. You will make design decisions within your area, drive them to production, and establish the technical direction for engineers working in your subsystem.
Key responsibilities include:
- Taking a major, ambiguous subsystem from design through production at scale
- Owning the design, delivery, and quality of your subsystem, including how it interfaces with the rest of the engine
- Driving design and code reviews in your area and raising the engineering bar around you
- Mentoring engineers and leading workstreams through influence
- Partnering with product, security R&D, and SecOps to turn customer problems into subsystem design
- Establishing AI safety, security, and guardrails for agentic components of your subsystem
- Defining and owning metrics that prove your subsystem works (e.g., entity-resolution accuracy, calibration quality, path-ranking precision)
You will work in a culture that values AI-first thinking, clean architecture, intuitive experiences, and continuous learning.
REQUIREMENTS:
- 6+ years of software engineering experience, including leading the design and delivery of complex production components
- Demonstrated experience as the technical owner or lead for a significant system or subsystem
- 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)
- Proven delivery of an ambiguous problem to a reliable production system that others depend on
- Sound judgment to make 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
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience
- Applied interest in security problems (attack-path analysis, vulnerability management, identity security, threat intelligence, or detection and response) is preferred
- Cybersecurity or security-product experience, or familiarity with modern security architectures and operations, is strongly preferred
- Experience with AI-assisted development tools and coding agents (Claude Code, Codex, Cursor, Windsurf) is a plus
- Experience with AI evaluation, safety, governance, or policy guardrails is a plus
