Staff Machine Learning Engineer, Voice AI

<h3><strong>About the Role</strong></h3> <p>Together AI is building the best inference infrastructure for voice applications. Our Voice AI platform powers production-grade, real-time voice agents and applications — serving speech-to-text and text-to-speech models with best-in-class latency and reliability.</p> <p>We&39;re looking for a Staff ML Engineer to drive the model serving layer for voice workloads. You&39;ll work hands-on with inference engines like TRT-LLM and SGLang to optimize how we serve models like Whisper, Parakeet, Orpheus, and Kokoro — pushing latency and throughput to the frontier. You&39;ll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly.</p> <p>This is a foundational hire on a small, high-impact team. Voice inference has unique challenges — streaming audio, tokenization, real-time latency budgets — that require dedicated ML engineering focus. You&39;ll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech.</p> <ul> <li>Own the model serving stack that powers Together&39;s voice platform across STT, TTS, and speech-to-speech.</li> <li>Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference.</li> <li>Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together&39;s infrastructure.</li> <li>Build quality evaluation frameworks that guide model selection for customers and inform the roadmap.</li> <li>Join a small, early-stage team with outsized impact on a fast-growing product area.</li> </ul> <p class="font-claude-response-body break-words whitespace-normal leading-1.7"> </p> <p class=&q