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职位ServiceNow

Staff Machine Learning Engineer - VoIP Infrastructure

ServiceNow

Staff Machine Learning Engineer - VoIP Infrastructure

ServiceNow

Atlanta

·

On-site

·

Full-time

·

3d ago

What you get to do in this role:

PLATO (Platform Engineering and AI Technology Organization) at Service Now is a customer-focused innovative group building intelligent software using a variety of technology stacks to enable end-to-end, industry-leading work experiences for our customers. We are a group of people deeply invested in the success of our customers that happen to have expertise and knowledge in advanced technologies and software engineering best practices. We are data driven, structured, committed and we enjoy what we are doing. We prioritize robustness, performance and user experience over the technology stack and tools.

We are a group of technology professionals and platform engineers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future.

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, Go Lang, 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
  • Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
  • Experience in using AI productivity tools such as Cursor, Windsurf, etc

For positions in this location, we offer a base pay of $173,100 - $303,000, 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 residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

Service Now is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, 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 globaltalentss@servicenow.com 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), Service Now may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon Service Now obtaining any export license or other approval that may be required by relevant export control authorities.

From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — Service Now stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

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关于ServiceNow

ServiceNow

ServiceNow, Inc. is an American software company that supplies a cloud computing platform for the creation and management of automated business workflows. The company was founded in Santa Clara, California, United States, in 2003 by Fred Luddy.

10,001+

员工数

Santa Clara

总部位置

$150B

企业估值

评价

3.8

10条评价

工作生活平衡

3.2

薪酬

3.8

企业文化

4.1

职业发展

3.4

管理层

3.6

72%

推荐给朋友

优点

Supportive and collaborative team environment

Good training and learning opportunities

Flexible work arrangements

缺点

Work-life balance challenges and heavy workload

Fast-paced and stressful environment

Limited growth opportunities in some areas

薪资范围

56个数据点

Junior/L3

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Data Scientist IC1

0份报告

$117,503

年薪总额

基本工资

-

股票

-

奖金

-

$99,878

$135,128

面试经验

4次面试

难度

3.8

/ 5

时长

14-28周

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Behavioral Interview

5

Panel Interview

6

Final Round Interview

常见问题

Coding/Algorithm

Behavioral/STAR

Technical Knowledge

System Design