Hybrid Tech Lead – ASR, TTS, Speech LLM, IC, Mentor

Posted last week

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About the role

  • Lead the end-to-end technical development of speech models (ASR, TTS, Speech-LLM) — from architecture, training strategy, and evaluation to production deployment.
  • Act as an individual contributor and mentor, guiding a small team working on model training, synthetic data generation, active learning, and inference optimization for healthcare applications.
  • Spearhead the technical development of speech models.

Requirements

  • Deep expertise in speech models (ASR, TTS, Speech LLM) and training frameworks (PyTorch, NeMo, ESPnet, Fairseq).
  • Proven experience with streaming RNN-T / CTC architectures, LoRA/adapters, and TensorRT optimization.
  • Telephony robustness: Codec augmentation (G.711 μ-law, Opus, packet loss/jitter), AGC/loudness norm, band-limit (300–3400 Hz), far-field/noise simulation.
  • Strong understanding of telephony noise, codecs, and real-world audio variability.
  • Experience in Speaker Diarization, turn detection model, smart voice activity detectionEvaluation: WER/latency curves, Entity-F1 (names/DOB/meds), confidence metrics.
  • TTS : VITS/FastPitch/Glow-TTS/Grad-TTS/StyleTTS2, CosyVoice/NaturalSpeech-3 style transfer, BigVGAN/UnivNet vocoders, zero-shot cloning.
  • Speech LLM: Model development and integration with Voice agent pipeline.
  • Experience deploying models with Triton Inference Server, Kubernetes, and GPU scaling.
  • Hands-on with evaluation metrics (WER, F1 on entities, latency p50/p95).
  • Familiarity with LM biasing, WFST grammars, and context injection.
  • Strong mentorship and code-review discipline.

Benefits

  • None specified

Job title

Tech Lead – ASR, TTS, Speech LLM, IC, Mentor

Job type

Experience level

Senior

Salary

Not specified

Degree requirement

Postgraduate Degree

Location requirements

HybridSingapore

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