Staff Machine Learning Engineer

ServiceNow•Santa Clara, CA

18h•$176,100 - $308,200

About The Position

The Staff Machine Learning Engineer will work in ServiceNow’s AI Engineering and Delivery group, building agentic AI and enterprise-scale search systems for Now Assist, AI Agents, and other AI-driven experiences. The role focuses on production-grade AI platform infrastructure, with emphasis on reliability, performance, safety, and customer impact at Fortune 500 scale. The engineer will design, build, and operate agentic systems embedded across the ServiceNow platform. This includes multi-agent orchestration, tool use, planning, memory, and failure recovery; grounding agent decisions in enterprise data such as CMDB, Workflow Data Fabric, and Knowledge Graph; and implementing observability, human-in-the-loop controls, and compliance safeguards. The role also involves retrieval and grounding, integration and evaluation of frontier models, and technical leadership through architecture decisions, code reviews, and coaching.

Requirements

5+ years of software engineering experience, with strong fundamentals in data structures, algorithms, and distributed systems.
Hands-on experience designing, shipping, and operating agentic systems in production, including multi-agent orchestration, tool calling, planning loops, memory, and failure recovery.
Production-grade Python skills.
Working experience with frontier AI SDKs such as Anthropic, Google, or OpenAI, including prompt engineering, structured outputs, and model evaluation in production settings.
Familiarity with production RAG and retrieval patterns, including vector stores, hybrid search, and retrieval evaluation metrics.
Track record of technical leadership, including architecture ownership, raising the code quality bar, and mentoring engineers on production AI practices.

Nice To Haves

Deeper specialization in search and retrieval at scale or MLOps/model observability.
Published work or open-source contributions in agentic systems or retrieval.
Exposure to LLM fine-tuning or inference optimization in production.
Experience with a systems language such as Go, Java, or C++.

Responsibilities

Design, build, and operate production-grade agentic AI systems embedded across the ServiceNow platform.
Design and ship multi-agent systems involving orchestration, tool use, planning loops, memory, and failure recovery.
Build agents that use ServiceNow enterprise data, including CMDB, Workflow Data Fabric, and Knowledge Graph, to make contextual decisions.
Own safety and governance guardrails, including observability, human-in-the-loop controls, and compliance infrastructure.
Work with the search team on retrieval grounding, including RAG pipelines, hybrid search, re-ranking, and evaluation.
Integrate frontier models into the Sense → Decide → Act → Govern architecture and evaluate cost, latency, and capability trade-offs for production use cases.
Provide technical leadership through architecture decisions, code reviews, raising code quality, and coaching engineers on production AI practices.