SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
ServiceNow is seeking a Staff Machine Learning Engineer to contribute to the design, development, and implementation of VoIP infrastructure and telephony platforms that power AI-driven voice workloads. You will collaborate with engineering, product, and infrastructure teams to ensure voice and AI platforms perform efficiently, scale reliably, and integrate seamlessly across SIP/RTP, Kamailio, RTPEngine, and related telecom systems.
Key responsibilities include:
- Design and implement VoIP infrastructure and observability features for AI-driven voice workloads
- Collaborate across engineering, product, and infrastructure teams on voice and AI platform performance, scalability, and integration
- Improve SRE practices by translating operational telephony and AI use cases into software tooling requirements
- Execute deployment and support activities for VoIP systems and AI/ML developers in production voice environments
- Build high-quality, scalable, reusable code following best practices in software architecture, code reviews, and unit testing
- Partner with product owners on detailed requirements and own code from design through delivery, spanning telephony infrastructure and LLM integration layers
- Mentor colleagues and promote knowledge-sharing across telecom and AI engineering disciplines
This role offers the opportunity to work at the intersection of telecommunications infrastructure and modern AI/ML systems, integrating large language models into real-time voice platforms at scale.
REQUIREMENTS:
- 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
- Assets: DevOps tooling experience (Helm, Ansible, Kubernetes, Prometheus, Splunk, GitLab CI); experience building software for compliance and security in regulated environments; 4+ years of infrastructure and platform operations, deployments, SRE, and DevOps with focus on platform health
