Staff Machine Learning Engineer - VoIP Infrastructure
About The Position
As a Staff Machine Learning Engineer focused on VoIP infrastructure, you will contribute to designing, developing, and implementing telephony platforms, VoIP infrastructure, and observability features that support AI-driven voice workloads. You will work across engineering, product, and infrastructure teams to help voice and AI platforms operate efficiently, scale reliably, and integrate with SIP/RTP, Kamailio, RTPEngine, and related telecom systems. The role includes improving SRE practices by translating operational telephony and AI workload needs into software-tooling requirements, and supporting VoIP systems and AI/ML developers working in production voice environments. You will own code from design through implementation, test automation, and delivery across telephony infrastructure and LLM integration layers, while promoting engineering best practices. You will also mentor colleagues and encourage knowledge-sharing across telecom and AI engineering.
Requirements
- Hands-on experience building VoIP systems using SIP/RTP protocols.
- Practical knowledge of Kamailio, RTPEngine, FreeSWITCH, SBCs, and PSTN systems, or similar technologies.
- Working knowledge of PSTN infrastructure and telecom protocols.
- Experience integrating applications on top of existing LLMs; building models is not required.
- Experience in prompt engineering and developing LLM-based features.
- At least 4 years of development experience with Python, GoLang, Java, or similar languages.
- At least 4 years of experience operating highly available distributed workloads on Kubernetes using a DevOps approach.
- Working experience building distributed systems with cloud-native software.
- Experience with software-defined networking, infrastructure as code, and configuration management.
Nice To Haves
- Experience with DevOps tooling such as Helm, Ansible, Kubernetes, Prometheus, Splunk, or GitLab CI.
- Experience building software for compliance and security in regulated environments.
- At least 4 years of experience with infrastructure and platform operations, deployments, SRE, and DevOps, with a continued focus on improving platform health.
Responsibilities
- Contribute to the design, development, and implementation of VoIP infrastructure, telephony platforms, and observability features for AI-driven voice workloads.
- Collaborate with engineering, product, and infrastructure teams to ensure voice and AI platforms perform efficiently, scale reliably, and integrate with SIP/RTP, Kamailio, RTPEngine, and related telecom systems.
- Improve SRE practices by turning operational telephony and AI workload use cases into requirements for software tooling.
- Contribute to deployment and support activities for VoIP systems and AI/ML developers operating in production voice environments.
- Build clean, scalable, reusable, high-quality code and follow software engineering best practices, including code reviews and unit testing.
- Work with product owners to understand requirements and own code through design, implementation, test automation, and delivery across telephony infrastructure and LLM integration layers.
- Integrate LLMs into voice platforms and real-time communication systems.
- Mentor colleagues and promote knowledge-sharing across telecom and AI engineering disciplines.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
