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Senior Staff Machine Learning Engineer

ServiceNow
Santa Clara, USA
Full-time
Senior · 10+ years experience
Onsite
Discovered 5 days ago
javapythonservicenowtypescript

Full Job Posting

What you’ll do

  • Lead zero-to-one work at production scale: turn an ambiguous, novel problem into a reliable system other teams build on, and set the bar where no precedent exists.
  • Drive technical direction across architecture, design, and code reviews, and raise the engineering bar across the incubation.
  • Mentor senior engineers and lead by influence, not title.
  • Partner with product, security R&D, SecOps to turn customer problems into architecture, and translate that architecture into decisions leaders can act on.
  • Establish AI safety, security, governance, and guardrails for agentic systems running in production.

What you bring

  • A track record of owning architecture across a large system or multiple teams, with deep experience operating production-quality software.
  • Hands-on depth in both agentic and LLM systems and probabilistic or ML-driven scoring—graph modeling, calibration, search and optimization, or risk and probability engineering.
  • Proven zero-to-one at scale: you’ve taken an ambiguous problem to a reliable production system that others depend on.
  • The judgment to make consequential architecture decisions under uncertainty, and make them defensible to engineers and executives alike.
  • Command of distributed systems, APIs, cloud-native development, and data or graph systems.
  • Expert-level Python, and/or Java, Go, or TypeScript.
  • Technical leadership and mentorship that moves teams through influence.
  • Applied interest in security problems—attack-path analysis, vulnerability management, identity security, threat intelligence, or detection and response—is strongly 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.
  • 10+ years of software engineering experience, including leading the design and delivery of complex production systems.
  • The 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.
  • Demonstrated experience as the technical owner or lead for a major system or across teams.
  • 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 harness and 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 $201,300 - $352,300, 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.
  • Work Personas
  • We 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.

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