Senior Staff Machine Learning Engineer_Voice AI

ServiceNow•Santa Clara, CA

2d•$201,300 - $352,300

About The Position

ServiceNow is hiring a Senior Staff Machine Learning Engineer focused on Voice AI. The role contributes to the design, development, and implementation of the core Voice Platform, including audio acquisition, conversation management, speech generation, integrations with API and self-hosted Voice AI models, and the Voice Harness. The engineer partners with product managers and customers to understand use cases and technical challenges, then builds solutions to support customer success. The position builds and deploys large-scale, distributed Voice AI systems across multiple regions and datacenters. It also emphasizes high-quality, clean, scalable, reusable software; engineering best practices; and continuous improvement of site reliability engineering through software tooling. The role includes mentoring colleagues and encouraging knowledge-sharing across Voice AI engineering disciplines.

Requirements

12+ years of relevant industry experience.
Hands-on experience building distributed Voice AI systems at large operational scale.
4+ years building LLM-based applications, integrating models rather than training them.
4+ years of development experience with Python, Golang, Java, or similar languages.
2+ years of experience building agents using prompt engineering and developing LLM-based experiences.
Experience operating highly available distributed workloads on Kubernetes using a DevOps approach.
Critical thinking about AI integrations for work processes, decision-making, or problem-solving, including using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact.

Nice To Haves

Experience building software for compliance and security in regulated environments.
Experience building with AI tools such as Claude Code, Cursor, or Windsurf.

Responsibilities

Contribute to the design, development, and implementation of the core Voice Platform, including audio acquisition, conversation management, speech generation, model integrations, and the Voice Harness.
Partner with product managers and customers to understand use cases and technology challenges and build solutions for customer success.
Build and deploy large Voice AI distributed systems at scale across multiple regions and datacenters.
Develop clean, scalable, reusable code and enforce software engineering best practices, including code reviews and unit testing.
Contribute to continuous improvement of the SRE practice by translating operational use cases into requirements for software tooling.
Mentor colleagues and promote knowledge-sharing across Voice AI engineering disciplines.