
Staff Machine Learning Engineer - VoIP Infrastructure
Boston, MAFull-timePosted 1w agoStill listed 6 days ago
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Job overview
The Staff Machine Learning Engineer - VoIP Infrastructure contributes to the design and implementation of telephony platforms, VoIP infrastructure, and observability features for AI-driven voice workloads. The role spans SIP/RTP systems, LLM integration, production deployment and support, and software engineering practices. It also contributes to SRE improvements and mentors colleagues across telecom and AI engineering disciplines.
Skills & qualifications
Skills
Qualifications
Full job description
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
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. From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.
How this job compares
Set against the 5,888 open Machine Learning Engineer jobs on Olive Jobs, counted October 27, 2026.
- Pay
- This postingNot listed
- Massachusetts median$150–225K/yr145 salary ranges
- US median$31–78/hr133 hourly ranges
- Openings
- Olive Jobs lists 169 open Machine Learning Engineer jobs in Massachusetts and 5,888 across the US. 5% of them nationwide are listed as remote or flexible.
- Hiring the most in Massachusetts
- Capital One31 open
- Amazon19 open
- Accenture7 open
- Experience
- This posting asks for at least 4 years of experience; Machine Learning Engineer postings that state a minimum ask for 5 years at the median (4,725 postings).
- Education
- 2,412 of the 5,888 open Machine Learning Engineer jobs (41%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 27, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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