Staff Machine Learning Engineer_Voice AI Engineer

ServiceNow•Santa Clara, CA

16h•$176,100 - $308,200•Hybrid

About The Position

ServiceNow is seeking a Staff Machine Learning Engineer specializing in Voice AI. This role involves contributing to the design, development, and implementation of the core Voice Platform, including Audio Acquisition, Conversation Management, Speech Generation, integration with APIs and self-hosted Voice AI models, and Voice Harness. The engineer will partner with product managers to understand customer use cases and challenges, build and deploy large-scale Voice AI distributed systems, and write high-quality, scalable code. A key aspect of the role is contributing to the continuous improvement of SRE practices and mentoring colleagues. ServiceNow is building an AI-native culture where technology and talent are unstoppable together, aiming to free people from busywork so they can focus on meaningful work.

Requirements

8+ year of relevant industry experience
Hands-on experience building distributed Voice AI systems with a large operational scale
4+ years building LLM-based applications (integrating models, not training)
4+ years of development experience with Python, Golang, Java, or similar languages.
2+ years of experience building agents (prompt engineering) and developing LLM-based experiences
Working experience operating highly available distributed workloads on Kubernetes following a DevOps approach.
Critically thinking around AI integrations for work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
Experience building with AI tools such as Claude Code, Cursor, Windsurf

Nice To Haves

Experience building software for compliance and security in regulated environments is considered an asset

Responsibilities

Contribute to the design, development and implementation of the core Voice Platform (Audio Acquisition, Conversation Management, Speech Generation, integration with API and self-hosted Voice AI models, Voice Harness)
Partner with product managers to work with customers, understand their use cases and technology challenges, and build for their success
Build and deploy large Voice AI distributed systems at scale spanning multiple regions and datacenters
Build high-quality, clean, scalable and reusable code by enforcing best practices around software engineering architecture and processes (Code Reviews, Unit testing, etc.)
Contribute to the continuous improvement of the SRE practice by turning operational use cases into requirements for software tooling
Be a mentor for colleagues and help promote knowledge-sharing across Voice AI engineering disciplines