Staff Machine Learning Engineer, Voice AI

📋 Description Own the voice inference roadmap end-to-end for STT, TTS, and speech-to-speech. Drive best-in-class inference performance for voice workloads (latency and throughput). Lead productionization of voice models at scale with serverless and dedicated endpoints. Build the voice evaluation platform for WER, latency, and naturalness across accents and noise. Shape architecture for next-gen model support (audio-native LLMs, SNAC/Encodec). Serve as technical DRI for model partner integrations (Cartesia, Deepgram, Rime). 🎯 Requirements 8+ years of ML engineering experience focused on model serving at production scale. Deep expertise in LLM serving engines (vLLM, SGLang, TensorRT-LLM) or equivalent. Expert-level Python and PyTorch; strong GPU optimization (CUDA, profiling). Proven system design judgment with scalable architectural decisions. Strong technical leadership; high autonomy and engineering quality. Familiarity with audio codecs/tokenization (SNAC/Encodec/DAC) is a plus. 🎁 Benefits Startup equity Health insurance