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About the role
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.
What they're looking for
- 5+ years of experience in ML engineering, with a focus on model serving, inference optimization, or ML infrastructure
- Hands-on experience with LLM serving engines (vLLM, SGLang, TensorRT-LLM, or similar) — comfortable reading and modifying engine internals, not just using APIs
- Strong proficiency in Python and PyTorch, experience with GPU profiling and optimization (CUDA, memory management, kernel-level debugging)
- Track record of shipping ML systems to production with measurable performance improvements
- Strong product sense — you think about what developers building voice apps actually need, not just what's technically interesting
- Comfort working on a small, early-stage team where you'll wear multiple hats and move fast
More about this role
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.
- Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech.
- Work directly with...
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