Senior Machine Learning Engineer, Voice AI

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. We're looking for a Senior ML Engineer to drive the model serving layer for voice workloads. You'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'll profile GPU utilization, design batching strategies for streaming audio, and ensure new model architectures can go from research to production quickly. 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'll shape how Together serves voice models as the industry moves from pipeline architectures (ASR → LLM → TTS) toward end-to-end speech-to-speech. Responsibilities include optimizing inference performance for voice models, productionizing voice models on serverless and dedicated endpoints, building and maintaining a voice model evaluation framework, enabling new model architectures, collaborating with model partners, profiling and debugging performance, and contributing to voice model fine-tuning capabilities. Requirements include 5+ years of experience in ML engineering, hands-on experience with LLM serving engines, strong proficiency in Python and PyTorch, a track record of shipping ML systems to production, strong product sense, and familiarity with audio codecs and tokenization schemes. A Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field is required.