Staff Machine Learning Engineer - VoIP Infrastructure at ServiceNow

About the role

What will you do at ServiceNow?

Company Description

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work.

Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together.

And we're just getting started.

Join us to put AI to work for people.

Job Description

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.

Qualifications

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.

Additional Information

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 residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance.

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.

Used under license.

Employee Type: Regular

Region: AMS - North America and Canada

Work Persona: Flexible

Which skills does this role require?

VoIPSIPRTPKamailioRTPEngineFreeSWITCHPythonGoLangJavaKubernetesDevOpsLLM integrationPrompt engineeringCloud-native softwareSREDistributed systemsPSTNLLMHelmAnsiblePrometheusSplunkGitLab CICloud-nativeSoftware-defined networkingInfrastructure as codeTelephonyObservabilityAIMachine learningScalabilityGoMachine LearningLLMs

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