Machine learning engineer in voice and video AI

Telnyx is an industry leader that's not just imagining the future of global connectivity—we're building it. From architecting and amplifying the reach of a private, global, multi-cloud IP network, to bringing hyperlocal edge technology right to your fingertips through intuitive APIs, we're shaping a new era of seamless interconnection between people, devices, and applications.

• Evaluate, adapt, and deploy speech-to-speech and full-duplex video models, including expressive avatars and synchronized audiovisual generation.
• Improve natural interaction through better turn-taking, interruption handling, and responses to verbal and visual cues.
• Track emerging research and open-source releases, benchmark promising approaches, and fine-tune models for languages, accents, and specialized domains such as medical terminology.
• Build data and evaluation pipelines that demonstrate improvements in realistic conversations.
• Train and deploy models on state-of-the-art GPU hardware across Telnyx’s global infrastructure.
• Optimize streaming inference, GPU utilization, latency, and serving cost while maintaining conversational quality, audiovisual synchronization, and reliability.
• Own features from model experiments through backend services, APIs, data models, and customer portal interfaces.
• Use advanced coding agents and harnesses to implement, test, debug, and review changes across the stack.

• 6+ years in machine learning or related engineering, with production experience and depth in speech generation, speech-to-speech systems, video generation, or multimodal models.
• Strong Python and PyTorch skills and hands-on experience adapting pretrained models.
• Experience with streaming or latency-sensitive systems, rigorous evaluation, and the tradeoffs between model quality, responsiveness, reliability, and cost.
• You can turn research into practical engineering decisions.
• You’re comfortable working beyond the ML codebase—making backend and frontend changes, navigating unfamiliar repositories, and following a feature through to a working customer experience.
• You actively want to work with the latest coding agents and harnesses, improve your workflows as the tools evolve, and apply strong engineering fundamentals to verify and take responsibility for their output.

• You’ll work where AI, real-time communications, and infrastructure meet, with access to state-of-the-art hardware and a global deployment footprint.
• You’ll own both the models and the products they power, bringing advances in voice and video AI directly to customers around the world.