Tech Lead — ASR / TTS / Speech LLM (IC + Mentor)
Tasks
- Architect and optimize training recipes
- Collaborate with ML-ops for production readiness and observability
- Design data pipelines for synthetic and real data generation
- Develop model switcher and failover strategies
- Ensure Kubernetes autoscaling for concurrent streams
- Evaluate and benchmark speech models
- Implement WFST grammars for context biasing
- Implement language model biasing APIs
- Integrate models with Triton Inference Server
- Mentor engineers on model training and model serving best practices
- Optimize inference with TensorRT
- Own technical roadmap for ASR TTS and speech LLM model training
- Run evaluation cycles and drift monitoring
Perks/Benefits
Skills/Tech-stack
AGC | Active Learning | Activity Detection | Automatic Speech Recognition | CTC | Data Generation | G711 mu law | GPU scaling | Inference Optimization | Inference Server | Kubernetes | Language Model | Language Model Biasing | Latency | LoRA | Loudness normalization | Mu law | Multi objective CTC | NVIDIA TensorRT | Noise augmentation | Opus | PyTorch | RNN-T | Speaker Diarization | Speaker selection | Speech LLM | Speech Recognition | Synthetic Data Generation | Synthetic data | Telephony | TensorRT FP16 | TensorRT Optimization | Text to Speech | Triton Inference | Triton Inference Server | Voice Activity Detection | Voice Synthesis | WER | WFST
Education
Roles
Engineer | Lead | Learning Engineer | Machine Learning Engineer | Tech Lead
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