ServiceNow
Staff Machine Learning Engineer
$176K–$308K
Santa Clara, CALIFORNIA, United States · Staff · Full-time · Posted Oct 20, 2026
- Experience
- 6+ years of software engineering experience.
- Education
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience.
About the job
Own and take a major subsystem of a new exploitability-analysis engine—from design through production—using machine learning to prioritize security work by realistic attack paths.
What you'll do
- Design, deliver, and ensure the quality of a major subsystem, such as the probability core, exposure graph and entity resolution, or calibration and validation loop.
- Set technical direction, lead design and code reviews, and mentor engineers while delivering the subsystem to production at scale.
- Partner with product, security R&D, and SecOps to translate customer problems into subsystem design and establish AI safety and security guardrails.
What they ask for
- 6+ years of software engineering experience, including leading design and delivery of complex production components.
- Track record as the technical owner or lead of a significant system or subsystem, with proven delivery of reliable production systems.
- Hands-on depth in agentic and LLM systems and/or probabilistic or ML-driven scoring; command of distributed systems, APIs, cloud-native development, and data or graph systems.
- Expert-level Python, and/or Java, Go, or TypeScript.
Nice to have
- Applied security experience or interest, including attack-path analysis, vulnerability management, identity security, threat intelligence, or detection and response.
- Experience with AI-assisted development tools, AI evaluation, safety, governance, or policy guardrails.
Pay
$176,100 - $308,200 USD base salary
Tools
Python, Java, Go, TypeScript, RAG, embeddings, vector search, MLOps
AI focus
Build an AI/ML-powered exploitability engine using probabilistic or ML-driven scoring, graph analytics, and agentic/LLM capabilities; establish safety, security, and evaluation guardrails.
Model-written summary · the original posting is authoritative