Staff Machine Learning Engineer - VoIP Infrastructure

ServiceNow; Boston (MA); Hybrid; USD 170,000 - 230,000; Full time

Benefits offered by this job

Flexible work persona

Job summary

ServiceNow in Boston seeks a Staff Machine Learning Engineer for VoIP infrastructure to design and implement VoIP systems powering AI-driven voice workloads. You'll collaborate with cross-functional teams to ensure scalable, reliable voice and AI platforms across SIP/RTP, Kamailio, RTPEngine, and related telecom tech.

You will drive SRE improvements, deploy and support VoIP systems for production AI workloads, and mentor engineers while embedding best practices in software architecture and CI/CD

Qualifications

• Hands-on experience building VoIP systems using SIP/RTP protocols.
• Practical knowledge of Kamailio, RTPEngine, FreeSWITCH, SBCs, and PSTN systems.
• 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.

Responsibilities

• 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.

Skills

VoIP experience

SIP/RTP

LLM integration

Python/Go/Java

Kubernetes/DevOps

Distributed systems

IaC/Config mgmt

Prompts engineering

Tools

Kamailio

RTPEngine

FreeSWITCH

Job description

• Full-time
• Employee Type: Regular
• Region: AMS - North America and Canada
• Work Persona: Flexible

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 withengineering,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 developersoperatingin production voice environments.
• Build high-quality, clean,scalableand 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 ofKamailio,RTPEngine,FreeSWITCH,SBCs, andPSTNsystems(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 experienceoperatinghighly availabledistributed workloads on Kubernetes following a DevOps approach.
• Working experiencebuildingdistributed systemswith cloud-native software;
• Experience with software-defined networking, infrastructure as code and configurationmanagement;
• Experience with DevOpstooling(e.g. Helm / Ansible / Kubernetes / Prometheus /Splunk/ GitLab CI) is considered an asset
• Experiencebuilding software for compliance and security in regulatedenvironmentsis considered an asset
• 4+ years of experience with infrastructure and platform operations, deployments, SRE, and DevOps with a continued focus on improving Platformhealthis considered an asset

Additional Information

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 [e-mail] 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.

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