Staff Machine Learning Engineer_Voice AI

ServiceNow•Santa Clara, CA

About The Position

As a Staff Machine Learning Engineer on the Voice AI team at ServiceNow, you will contribute to the design, development, and implementation of the core Voice Platform, including audio acquisition, conversation management, speech generation, integration with API and self-hosted Voice AI models, and the Voice Harness. You will partner with product managers to understand customer use cases and technology challenges and build solutions for their success. The role involves building and deploying large-scale, distributed Voice AI systems across multiple regions and datacenters. You will write clean, scalable, reusable code and promote software engineering best practices, including code reviews and unit testing. You will also help continuously improve SRE practices by turning operational use cases into requirements for software tooling, and mentor colleagues while fostering knowledge-sharing across Voice AI engineering disciplines.

Requirements

At least 8 years of relevant industry experience.
Hands-on experience building distributed Voice AI systems at large operational scale.
At least 4 years of experience building LLM-based applications, integrating models rather than training them.
At least 4 years of development experience with Python, Golang, Java, or similar languages.
At least 2 years of experience building agents through prompt engineering and developing LLM-based experiences.
Working 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 use of AI-powered tools, workflow automation, analysis of AI-driven insights, or exploration of 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

Design, develop, and implement the core Voice Platform, including audio acquisition, conversation management, speech generation, integrations with API and self-hosted Voice AI models, and the Voice Harness.
Partner with product managers to understand customer use cases and technology challenges and build solutions for customer success.
Build and deploy large-scale Voice AI distributed systems spanning multiple regions and datacenters.
Develop clean, scalable, reusable code and apply software engineering best practices such as code reviews and unit testing.
Contribute to continuous improvement of SRE practices by translating operational use cases into software tooling requirements.
Mentor colleagues and promote knowledge-sharing across Voice AI engineering disciplines.