Staff Machine Learning Engineer - VoIP Infrastructure

ServiceNow•Dallas, TX

28d•$176,100 - $308,200

About The Position

As a Staff Machine Learning Engineer focused on VoIP infrastructure, you will help design, develop, and implement VoIP infrastructure, telephony platforms, and observability features for AI-driven voice workloads. You will collaborate with engineering, product, and infrastructure teams to ensure voice and AI platforms perform efficiently, scale reliably, and integrate with SIP/RTP, Kamailio, RTPEngine, and related telecom systems. You will contribute to SRE improvements by translating operational telephony and AI workload use cases into software tooling requirements, and support deployment and production operations for VoIP systems and AI/ML developers. You will write clean, scalable, reusable code and apply software engineering best practices, including code reviews and unit testing. Working with product owners, you will own work from design through implementation, test automation, and delivery across telephony infrastructure and LLM integration layers. The role also includes integrating LLMs into voice platforms and real-time communication systems, and mentoring colleagues to encourage knowledge-sharing across telecom and AI engineering disciplines.

Requirements

Hands-on experience building VoIP systems using SIP/RTP protocols.
Practical knowledge of Kamailio, RTPEngine, FreeSWITCH, SBCs, and PSTN systems, or similar technologies.
Working knowledge of PSTN infrastructure and telecom protocols.
Experience integrating applications on top of existing LLMs; model-building experience is not required.
Experience in prompt engineering and developing LLM-based features.
At least 4 years of development experience with Python, GoLang, Java, or similar languages.
At least 4 years of experience operating highly available distributed workloads on Kubernetes using a DevOps approach.
Working experience building distributed systems with cloud-native software.
Experience with software-defined networking, infrastructure as code, and configuration management.

Nice To Haves

Experience with DevOps tooling such as Helm, Ansible, Kubernetes, Prometheus, Splunk, or GitLab CI.
Experience building software for compliance and security in regulated environments.
At least 4 years of experience with infrastructure and platform operations, deployments, SRE, and DevOps, with an ongoing focus on improving platform health.

Responsibilities

Contribute to the design, development, and implementation of VoIP infrastructure, telephony platforms, and observability features for AI-driven voice workloads.
Collaborate with engineering, product, and infrastructure teams to ensure voice and AI platforms perform efficiently, scale reliably, and integrate with SIP/RTP, Kamailio, RTPEngine, and related telecom systems.
Contribute to continuous SRE improvement by turning operational telephony and AI workload use cases into software tooling requirements.
Contribute to deployment and support activities for VoIP systems and AI/ML developers operating in production voice environments.
Build high-quality, clean, scalable, reusable code and apply software engineering best practices, including code reviews and unit testing.
Work with product owners to understand requirements and own code from design through implementation, test automation, and delivery across telephony infrastructure and LLM integration layers.
Integrate LLMs into voice platforms and real-time communication systems.
Mentor colleagues and promote knowledge-sharing across telecom and AI engineering disciplines.