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

Jobtailor; Boston (MA); On-site; USD 180,000 - 260,000; Full time

Job summary

Jobtailor in Boston is seeking a leader to guide end-to-end development of ASR, TTS, and Speech LLMs, from architecture to production deployment.

You will mentor a small team focusing on training, synthetic data, active learning, and inference optimization for healthcare applications, and own the technical roadmap for STT/TTS/Speech LLM.

Qualifications

• 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.

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.
• Own the technical roadmap for STT/TTS/Speech LLM model training.

Education

M.S. / Ph.D. in Computer Science

Speech Processing

Tools

Triton Inference Server

Kubernetes

GPU Scaling

Fairseq

ESPnet

Job description

• 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