{"id":2342299,"url":"https://alion.io/job/servicenow-staff-machine-learning-engineer-6","title":"Staff Machine Learning Engineer","company":{"id":97,"name":"ServiceNow","domain":"servicenow.com","url":"https://alion.io/company/servicenow","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":80,"open_postings":32,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":17,"computed_at":"2026-10-14T06:34:16Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Santa Clara, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":176100,"max":308200,"currency":"USD","period":"year","gross":null,"usd_annual":308200},"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AI Agents","optional":false},{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"OpenAI Codex","optional":false},{"name":"Python","optional":false},{"name":"ServiceNow","optional":false},{"name":"TypeScript","optional":false},{"name":"Windsurf","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"Clean Architecture","optional":true},{"name":"Embeddings","optional":true},{"name":"Machine Learning","optional":true},{"name":"RAG","optional":true}],"status":"live","first_seen_at":"2026-09-12T00:02:35Z","employer_posted_date":"2026-09-12","last_verified_at":"2026-10-14T02:17:53Z","board_verified":true,"closed_at":null,"days_open":32,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":32},"description":"It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone-freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow- helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.\nJoin us to put AI to work for people.\nAbout the team\nThe 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.\nThis 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.\nThe role\nAs 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.\nWhat you’ll own\nA 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. \nThe design decisions within your subsystem, and how it interfaces with the rest of the engine. \nThe metrics that prove your subsystem works-entity-resolution accuracy, calibration quality, or path-ranking precision-owned as first-class targets. \nTechnical direction for the engineers working in your area. \nWhat you’ll do\nTake a major, ambiguous subsystem from design through production at scale. \nDrive design and code reviews in your area, and raise the engineering bar around you. \nMentor engineers and lead a workstream through influence. \nPartner with product, security R&D, and SecOps to turn customer problems into subsystem design. \nEstablish AI safety, security, and guardrails for the agentic parts of your subsystem. \nWhat you bring\nA track record of owning a significant system or subsystem end-to-end in production. \nHands-on depth in agentic and LLM systems and/or probabilistic or ML-driven scoring-graph modeling, calibration, search and optimization. \nProven delivery of an ambiguous problem to a reliable production system that others depend on. \nThe judgment to make sound design decisions under uncertainty within your area. \nCommand of distributed systems, APIs, cloud-native development, and data or graph systems. \nExpert-level Python, and/or Java, Go, or TypeScript. \nTechnical leadership that moves a workstream through influence. \nApplied interest in security problems-attack-path analysis, vulnerability management, identity security, threat intelligence, or detection and response-is preferred. \nExperience with AI-assisted development tools and coding agents such as Claude Code, Codex, Cursor, or Windsurf is a plus. \nExperience with AI evaluation, safety, governance, or policy guardrails is a plus. \n 6+ years of software engineering experience, including leading the design and delivery of complex production components. \nDemonstrated experience as the technical owner or lead for a significant system or subsystem. \nDepth building AI/ML-powered production systems; probabilistic modeling, graph analytics, or calibration and evaluation is a strong plus. \nModern AI experience: LLMs, RAG, embeddings, vector search, agentic workflows, model evaluation, or AI observability. \nStrong programming experience in Python and/or Java, Go, or a similar language. \nCloud-native technologies, distributed systems, APIs, databases, and scalable architectures. \nBachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience. \nCybersecurity or security-product experience, or familiarity with modern security architectures and operations, is strongly preferred. \nFor 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.\n Work Personas\nWe 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.\nEqual Opportunity Employer\nServiceNow 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.\nAccommodations\nWe 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  for assistance.\nExport Control Regulations\nFor 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.\nFrom Fortune. ©2026 Fortune Media IP Limited. All rights reserved. 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