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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Machine Learning Engineer - **Company:** ServiceNow - **Location:** Santa Clara, CA, United States - **Salary:** $240,100.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Mobile Application Development, Cloud Engineering, Cyber Security, Cursor (Graphical User Interface Elements), Distributed Systems, Identity and Access Management, Intrusion Detection and Prevention, Python (Programming Language), Machine Learning, Software Safety, Software Engineering, Cloud Platform System, Large Language Models, Multi-Agent Systems, Model Validation, Information Technology, Servicenow, Microservices - **Published:** September 12, 2026 - **Apply:** https://jobs.smartrecruiters.com/ServiceNow/744000149124199-principal-machine-learning-engineer ## About the Role * Deep expertise in modern AI/ML with a track record of building production AI systems-LLMs, foundation models, agentic architectures, RAG, retrieval, and model evaluation-alongside probabilistic or ML-driven scoring. * The ability to set a compelling technical vision and drive it across teams, then go deep into architecture and code. * A proven record of turning ambitious, ambiguous ideas into products that scale to enterprise workloads. * An innovator's mindset-challenging conventional approaches and seizing the openings created by rapidly evolving AI. * Command of distributed systems, APIs, cloud-native platforms, and data or graph systems. * Expert-level Python and modern AI frameworks and infrastructure; experience with Java, Go, or similar languages is valuable. * Executive-level communication: able to articulate a compelling technical vision to engineers, customers, and senior leadership. * Applied depth in security problems-threat detection, vulnerability and exposure management, identity security, risk prioritization, or autonomous remediation-is strongly preferred. * Extensive use of AI-native development tools and coding agents such as Claude Code, Codex, Cursor, or Windsurf across the software development lifecycle., * 15+ years of software engineering experience, including significant technical and engineering leadership responsibility. * Demonstrated experience designing and delivering AI/ML-powered products and platforms in production. * Experience leading technical initiatives spanning multiple teams without direct authority. * Demonstrated ability to design systems that scale to enterprise workloads. * Hands-on experience with frontier LLMs, agent frameworks, retrieval and vector technologies, and model evaluation and observability; probabilistic modeling or graph analytics is a strong plus. * Strong backend engineering experience with distributed systems, APIs, microservices, and cloud-native architectures. * Extensive experience using AI-native development tools and coding agents as part of the software development lifecycle. * Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline, or equivalent practical experience. * Cybersecurity products, or deep familiarity with modern security architectures and security operations, is strongly preferred. ## Description As a Principal ML Engineer, you set the technical vision for exploitability-based security across the portfolio-not just one engine. You define the hardest modeling problems worth solving, set the direction other staff and senior engineers build within, and represent the work to executives, customers, and the broader engineering organization. What you'll own * The technical vision and architecture for exploitability-driven security: where the engine goes next, and the class of problems it should solve beyond any single release. * The hardest unsolved modeling problems-how calibrated attack-path probability holds up across environments, how identity and agent surfaces enter the model, and how ground truth feeds back into it. * The engineering standards and architectural direction that multiple teams build within: scalability, reliability, and the scientific rigor of the scoring. * The build-on strategy across the portfolio: what the engine reuses from existing products, what must be net-new, and why. What you'll do * Set technical direction across multiple teams without direct authority, and turn ambitious ideas into working, enterprise-grade products. * Explore and apply emerging AI to cybersecurity in fundamentally new ways-not simply bolt AI onto existing products. * Represent the team's technology and innovation with executives, customers, partners, and the broader engineering organization. * Mentor staff and senior engineers, and raise the overall engineering bar through coaching and technical leadership. * Champion AI-native engineering practices, including extensive use of coding agents and autonomous development, testing, evaluation, and operational workflows. * Set the direction for AI safety, security, governance, and guardrails for agentic systems running in production., 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. ## Related Videos - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [Thinking Differently - How to Make Money from Cyber Attacks & Cheats](https://www.wearedevelopers.com/videos/745-thinking-differently-how-to-make-money-from-cyber-attacks-cheats) - [Applying Agile Principles to Incident Management ](https://www.wearedevelopers.com/videos/101-applying-agile-principles-to-incident-management) - [Microservices: how to get started with Spring Boot and Kubernetes](https://www.wearedevelopers.com/videos/242-microservices-how-to-get-started-with-spring-boot-and-kubernetes) - [AI in Production: applied AI & enterprise use cases](https://www.wearedevelopers.com/videos/100130-ai-in-production-applied-ai-enterprise-use-cases) - [Cyber Security: Small, and Large!](https://www.wearedevelopers.com/videos/259-cyber-security-small-and-large) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? 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