[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All ServiceNow jobs](https://jobs.opennash.com/companies/servicenow/) · [Search jobs](/search/) ServiceNow · Santa Clara, CA # Staff Machine Learning Engineer Santa Clara, CALIFORNIA, United States Full-time Senior individual contributor $176,100 - $308,200 Data & Analytics Listed on ServiceNow’s official careers site. Posted September 12, 2026. Check that it is still open and apply there. [Apply on ServiceNow’s careers site →](https://jobs.smartrecruiters.com/ServiceNow/744000149124469-staff-machine-learning-engineer) [OpenNash Jobs](https://jobs.opennash.com/) / [ServiceNow](https://jobs.opennash.com/companies/servicenow/) / Staff Machine Learning Engineer ## Job description 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. 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. ## Qualifications 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. Depth building AI/ML-powered production systems; probabilistic modeling, graph analytics, or calibration and evaluation is a strong plus. ### 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, 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. ## At a glance - Posted by the employer: Sep 12, 2026 - First seen by OpenNash: Oct 10, 2026 - Last checked: Oct 17, 2026 - Listed for: 35 days - Location: Santa Clara, CALIFORNIA, United States - Employment type: Full-time - Pay: $176,100 - $308,200[Apply on ServiceNow’s careers site →](https://jobs.smartrecruiters.com/ServiceNow/744000149124469-staff-machine-learning-engineer) ## More jobs at ServiceNow ### [Machine Learning Engineer](https://jobs.opennash.com/companies/servicenow/jobs/1e838dd7cacc3000e73d/) Santa Clara, CALIFORNIA, United States ### [Principal Machine Learning Engineer](https://jobs.opennash.com/companies/servicenow/jobs/b02405e7d1c3e8252add/) Santa Clara, CALIFORNIA, United States ### [Senior Machine Learning Engineer, Agent Eval Platform](https://jobs.opennash.com/companies/servicenow/jobs/5f219cdd60bde8193a41/) Santa Clara, CALIFORNIA, United States ### [Senior Machine Learning Engineer_Linguistics and Speech](https://jobs.opennash.com/companies/servicenow/jobs/d4e3f9b3f26be2cbc57d/) Santa Clara, CALIFORNIA, United States ### [Senior Staff Data Platform Engineer - Data Access Team](https://jobs.opennash.com/companies/servicenow/jobs/c7867f0cac9922db23db/) Santa Clara, CALIFORNIA, United States ## Similar jobs at other companies ### [Senior Staff Engineer, Machine Learning Engineering ( On-device Learning SW)](https://jobs.opennash.com/companies/qualcomm/jobs/d561df305202050c72d5/) Qualcomm · San Diego, California, United States of America ### [Staff Machine Learning Software Engineer](https://jobs.opennash.com/companies/qualcomm/jobs/1c015546a5addf14b5ac/) Qualcomm · San Diego, California, United States of America ### [AI Machine Learning Engineering Staff](https://jobs.opennash.com/companies/lockheed-martin/jobs/a50fa89c9d061673bf86/) Lockheed Martin · Virtual Three, TX ### [A/AI Machine Learning Engineering Staff - Clearance Required](https://jobs.opennash.com/companies/lockheed-martin/jobs/fee14b837ea19e8438a2/) Lockheed Martin · Huntsville, AL ### [Senior Machine Learning Engineer](https://jobs.opennash.com/companies/microsoft/jobs/a28bc03521860e161cf2/) Microsoft · United States, Massachusetts, Cambridge OpenNash lists jobs from employers’ own careers sites and does not handle applications. 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