Staff Machine Learning Engineer- Voice AI

What you get to do in this role:

The Advanced Technology Group (ATG) at ServiceNow is a customer-focused innovation group building intelligent software and smart user experiences using existing and latest advanced technologies to enable end-to-end, industry-leading work experiences for customers. We are a group of researchers, applied scientists, engineers, and product managers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future.

You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that any user, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world.

• 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

To be successful in this role you have:

• Experience in leveraging or critically thinking about how to integrate AI into 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.
• 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)
• 6+ 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. 
• Experience building software for compliance and security in regulated environments is considered an asset
• A proven track record of architecting and shipping distributed Voice AI or voice platform systems (real-time audio, STT/TTS, telephony or WebRTC) at large operational scale
• 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