Staff Machine Learning Engineer - VoIP Infrastructure

As a Staff Machine Learning Engineer - VoIP Infrastructure you will:  • Contribute to the design, development and implementation of VoIP infrastructure, telephony platforms, and observability features that power AI-driven voice workloads   • Collaborate with engineering, Product, and infrastructure teams to ensure our voice and AI platforms perform efficiently, scale reliably, and integrate seamlessly across SIP/RTP, Kamailio, RTPEngine, and related telecom systems.   • Contribute to the continuous improvement of the SRE practice by turning operational telephony and AI workload use cases into requirements for software tooling.   • Contribute to the execution of deployment and support activities for VoIP systems and AI/ML developers operating in production voice environments.   • Build high-quality, clean, scalable and reusable code by enforcing best practices around software engineering architecture and processes (Code Reviews, Unit testing, etc.).   • Work with product owners to understand detailed requirements and own your code from design, implementation, test automation, and delivery — spanning both telephony infrastructure and LLM integration layers.   • Experience integrating LLMs into voice platforms and real-time communication systems.   • Be a mentor for colleagues and help promote knowledge-sharing across telecom and AI engineering disciplines.   To be successful in this role you have:  • Hands-on experience building VoIP systems using SIP/RTP protocols;     • Practical knowledge of Kamailio, RTPEngine, FreeSWITCH, SBCs, and PSTN systems (or similar);   • Working knowledge of PSTN infrastructure and telecom protocols;   • Experience integrating applications on top of LLMs (using existing models, not building them);   • Experience in prompt engineering and developing LLM based features    • 4+ years of development experience with Python, GoLang, Java or similar languages.   • 4+ years of experience operating highly available distributed workloads on Kubernetes following a DevOps approach.    • Working experience building distributed systems with cloud-native software;    • Experience with software-defined networking, infrastructure as code and configuration management;   • Experience with DevOps tooling  (e.g. Helm / Ansible / Kubernetes / Prometheus /Splunk/ GitLab CI) is considered an asset   • Experience building software for compliance and security in regulated environments is considered an asset   • 4+ years of experience with infrastructure and platform operations, deployments, SRE, and DevOps with a continued focus on improving Platform health is considered an asset     For positions in this location, we offer a base pay of $176,100 - $308,200 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location. Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here . To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residen