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Salary: USD 128,900 - 219,100 / annual
ServiceNow's Security and Risk Engineering organization is building a zero-to-one incubation: a novel exploitability engine that ranks security work by exploitability—where an attacker could realistically get in—rather than raw severity. This is a production ML system that turns raw security signal into ranked, reachable attack paths.
As a Senior ML Engineer, you will build core components of this engine, taking well-scoped problems from design to production and growing into deeper ownership as the system matures. You'll own specific subsystems such as evidence ingestion and connectors, entity resolution, graph construction, or parts of the probability core—all built to production quality.
Key responsibilities include:
- Designing, building, testing, and operating production ML components with strong engineering fundamentals
- Owning the correctness and reliability of what you ship: tests, evaluation, observability, and metrics that demonstrate component performance
- Turning ambiguous requirements into working code, with guidance on architectural decisions that shape the wider system
- Managing the data and model plumbing that keeps the graph accurate—entity-resolution quality, evidence provenance, and decay
- Contributing to design and code reviews, raising the quality bar on the team
- Prototyping quickly to evaluate new AI capabilities against real cybersecurity problems
- Partnering with product, security R&D, and SecOps to understand problems
- Applying AI safety, security, and guardrail practices to your work
The team values AI-first thinking, clean architecture, intuitive experiences, and continuous learning. You'll work on a distributed team with flexible work personas.
REQUIREMENTS:
- 3+ years of software engineering experience, or equivalent practical experience
- 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
- Experience with AI-assisted development tools (Claude Code, Codex, Cursor, Windsurf) is a plus
- Experience with AI evaluation, safety, or guardrails is a plus
