Senior Machine Learning Engineer, Voice AI

Job summary

Responsibilities

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.

• Own the model serving stack that powers Together's voice platform across STT, TTS, and speech-to-speech.
• Work directly with state-of-the-art accelerators (H100s, H200s, B200s) to optimize voice model inference.
• Collaborate with model partners (Cartesia, Deepgram, Rime, and others) to bring their models to production on Together's infrastructure.
• Build quality evaluation frameworks that guide model selection for customers and inform the roadmap.
• Join a small, early-stage team with outsized impact on a fast-growing product area.

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.

Tech stack

• vLLM
• Python
• PyTorch
• CUDA