{"id":2956420,"url":"https://alion.io/job/servicenow-senior-ml-engineer-3","title":"Senior ML 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":37,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":18,"computed_at":"2026-10-29T05:49:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","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":143200,"max":243400,"currency":"USD","period":"year","gross":null,"usd_annual":243400},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Claude Code","optional":false},{"name":"Cursor","optional":false},{"name":"Embeddings","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":"RAG","optional":false},{"name":"ServiceNow","optional":false},{"name":"TypeScript","optional":false},{"name":"Windsurf","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"AI Agents","optional":true},{"name":"Anomaly Detection","optional":true},{"name":"Clean Architecture","optional":true},{"name":"Machine Learning","optional":true}],"status":"closed","first_seen_at":"2026-10-20T14:29:40Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-28T02:58:27Z","board_verified":false,"closed_at":"2026-10-28T02:58:27Z","days_open":7,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":7},"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 Senior ML Engineer, you build core components of a novel exploitability engine-shipping production ML that turns raw security signal into ranked, reachable attack paths. You take well-scoped problems from design to production and grow into deeper ownership as the system matures.\nWhat you’ll own\nWell-scoped components of the engine-evidence ingestion and connectors, entity resolution, graph construction, or parts of the probability core-built to production quality. \nThe correctness and reliability of what you ship: tests, evaluation, observability, and the metrics that show your component works. \nTurning ambiguous requirements into working code, with guidance on the calls that shape the wider system. \nThe data and model plumbing that keeps the graph accurate-entity-resolution quality, evidence provenance, and decay. \nWhat you’ll do\nDesign, build, test, and operate production ML components with strong engineering fundamentals. \nContribute to design and code reviews, and help raise the quality bar on the team. \nPrototype quickly to evaluate new AI capabilities against real cybersecurity problems. \nPartner with product, security R&D, and SecOps to understand the problem behind the ticket. \nApply AI safety, security, and guardrail practices to what you build. \nWhat you bring\nSolid software engineering fundamentals and experience operating production-quality software. \nHands-on experience building ML- or LLM-powered applications-RAG, embeddings, agents, or probabilistic or ML-driven scoring. \nExperience taking a prototype to a reliable, maintainable production solution. \nWorking knowledge of distributed systems, APIs, cloud-native development, and data or graph systems. \nStrong Python, and/or Java, Go, or TypeScript. \nInterest in security problems-vulnerability management, identity security, threat detection, or risk prioritization. \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, or guardrails is a plus. \n 3+ years of software engineering experience, or equivalent practical experience. \nThe primary skills required are Predictive Modeling, Graph ML, Security Analytics, Anomaly Detection, Risk Scoring, LLMs/Agentic AI, and MLOps, which align with advanced machine learning and AI engineering rather than traditional software development.\nExperience designing and delivering production software systems. \nExperience building or integrating AI/ML-powered applications in a production or near-production environment. \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 is a plus. \nFor positions in this location, we offer a base pay of $143,200 - $243,400, 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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