Senior Software Engineer at Capital One collaborating across Agile teams to drive technological transformations. Focusing on full - stack development and delivering cloud - based solutions for financial empowerment.
About the role
- Tech Lead specializing in ASR, TTS, and Speech LLM for a healthcare technology company. Leading the technical development of speech models in a hybrid environment in Singapore.
Responsibilities
- 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
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