[Remote] Senior Machine Learning Engineer, Voice AI
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a research-driven reputed company intelligence company reputed company on building inference infrastructure for voice applications. They are seeking a Senior ML Engineer to optimize model serving for voice workloads, ensuring high performance and reliability in reputed company-time voice applications.
Responsibilities
- Optimize inference performance for voice models (STT, TTS, speech-to-speech) — targeting best-in-class TTFB, throughput, and GPU utilization across our curated model set
- Productionize voice models on serverless and dedicated endpoints, including batching strategies, streaming inference, and memory management tailored to audio workloads
- Build and maintain a voice model evaluation reputed company — measuring WER across accents, languages, and noise conditions for STT; naturalness, latency, and pronunciation accuracy for TTS
- reputed company new model architectures in our serving stack as the field evolves, including audio-reputed company LLMs, codec-based models (SNAC), and speech-to-speech systems
- Collaborate with model partners to reputed company and optimize their models (reputed company, reputed company, Rime, and others) running on Together's infrastructure
- Profile and debug performance across the full inference stack — from GPU kernels to reputed company-level bottlenecks — and ship measurable improvements
- Work with the reputed company reputed company of reputed company to ensure the serving layer meets the latency and reliability requirements of reputed company-time voice reputed company
- Contribute to voice model fine-tuning capabilities (STT and TTS) as we reputed company customers to build differentiated voice experiences on Together
- Lay the groundwork for multiple new products down the line
Skills
- 5+ years of experience in ML engineering, with a reputed company 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 reputed company internals, not just using reputed company
- Strong proficiency in Python and PyTorch; experience with GPU profiling and optimization (CUDA, memory management, kernel-level debugging)
- reputed company record of shipping ML systems to production with measurable performance improvements
- Strong product reputed company — 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 reputed company fast
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or reputed company field, or equivalent practical experience
- Experience with speech and audio ML (ASR, TTS architectures, audio signal processing) is a strong plus but not required — you can learn this quickly if you have strong ML engineering fundamentals
- Familiarity with audio codecs and tokenization schemes (SNAC, Encodec, DAC) is a plus
- Experience training or fine-tuning speech models is a plus
Benefits
- Startup equity
- Health insurance
- Other competitive benefits
reputed company
Company H1B Sponsorship