Staff 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

• 8+ years of ML engineering experience, with a demonstrated focus on model serving, inference optimization, or ML infrastructure at production scale — including systems you've…
• Deep, practical expertise in LLM serving engines (vLLM, SGLang, TensorRT-LLM, or equivalent) — you've modified engine internals, debugged edge cases under load, and contributed…
• Expert-level Python and PyTorch proficiency, with a strong command of GPU optimization — CUDA kernels, memory hierarchies, profiling toolchains — and a track record of turning…
• Proven system design judgment — you've made architectural decisions that held up at scale and influenced how a team or platform evolved; you can articulate the tradeoffs you made…
• Strong technical leadership — you operate with high autonomy, define the right problems before solving them, and raise the bar for engineering quality around you without…

Tech stack

• vLLM
• Python
• PyTorch
• CUDA