Senior Machine Learning Engineer (Voice & Video AI)

About Telnyx

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.

We're driven by a desire to transform and modernize what's antiquated, automate the manual, and solve real-world problems through innovative connectivity solutions. As a testament to our success, we're proud to stand as a financially stable and profitable company. Our robust profitability allows us not only to invest in pioneering technologies but also to foster an environment of continuous learning and growth for our team.

Our collective vision is a world where borderless connectivity fuels limitless innovation. By joining us, you can be part of laying the foundations for this interconnected future. We're currently seeking passionate individuals who are excited about the opportunity to contribute to an industry-shaping company while growing their own skills and careers.

The Impact You'll Drive

You’ll build the next generation of conversational voice and video AI: agents that can see, listen, speak, and respond naturally in real time. Your work will span speech-to-speech models, full-duplex audiovisual interaction, multilingual capabilities, and adaptation for specialized domains.

This is a hands-on applied AI role with end-to-end product ownership. You’ll take promising models from evaluation and fine-tuning into production on state-of-the-art GPU hardware across our global infrastructure, then build the functionality customers need to use them. Our AI engineers contribute across the stack—from inference services to backend APIs and frontend customer portal changes.

We expect state-of-the-art coding agents and development harnesses to be part of your everyday workflow. You’ll use them to move faster across codebases while owning the quality, correctness, and maintainability of what you ship.

What You’ll Work On

Real-time voice and video models: 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.

Applied research and model adaptation: 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.

Production performance at global scale: 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.

Complete product delivery: 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.

What You’ll Work With

Models and data: Python, PyTorch, open-source speech and multimodal models, audio and video processing pipelines, and distributed training and fine-tuning.

Infrastructure: State-of-the-art GPU hardware, globally deployed inference services, Docker, Kubernetes, and tools for profiling, optimization, and evaluation.

Product and development: Backend APIs, databases, frontend customer portals, and state-of-the-art coding agents and development harnesses.

You’ll help choose and evolve the stack as the models, tools, and product needs advance.

What We’re Looking For

Deep ML expertise: 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.

Strong systems judgment: 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.

End-to-end engineering ownership: 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.

An agent-driven development mindset: 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.

Why Telnyx

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.

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