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

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. Own the technical roadmap for STT/TTS/Speech LLM model training. Requirements M.S. / Ph.D. in Computer Science, Speech Processing, or related field. 7–10 years of experience in applied ML, at least 3 in speech or multimodal AI. Track record of shipping production ASR/TTS models or inference systems at scale. 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. Core Competencies Demonstrates deep expertise in developing and deploying speech models, including ASR, TTS, and Speech LLM, with a strong focus on production readiness and performance optimization. Proven ability to mentor teams and guide technical roadmaps in healthcare applications. Highest-signal resume keywords Speech Model Development Production ASR/TTS Model Shipping Applied Machine Learning Expertise Experience with PyTorch and NeMo Telephony Robustness and Noise Handling ATS Optimization Keywords Hard Skills ASR Model Development TTS Model Development Speech LLM Integration Streaming RNN-T Architectures TensorRT Optimization Evaluation Metrics (WER, F1) Speaker Diarization Turn Detection Model Smart Voice Activity Detection Codec Augmentation Soft Skills Mentorship Code Review Discipline Certifications & Qualifications M.S. / Ph.D. in Computer Science Speech Processing Industry Keywords Healthcare Applications Multimodal AI Telephony Noise Real-World Audio Variability Context Injection Tools & Technologies Triton Inference Server Kubernetes GPU Scaling Fairseq ESPnet #J-18808-Ljbffr Jobtailor