Lead Assistant Manager

Senior ASR/TTS Specialist - AI Agent Integration Expert

Company:

Position Summary

Senior ASR/TTS Specialist

Key Responsibilities

Speech AI Model Development & Integration

• Model Fine-tuning: Customize state-of-the-art ASR/TTS models for domain-specific applications with 300ms latency
• Speech-to-Speech Systems: Build end-to-end S2S pipelines using Amazon Nova Sonic v1.0, Azure OpenAI Realtime (GPT-4o), and Gemini 2.5 Flash Native Audio
• Multi-modal Integration: Develop speech models integrating with vision and text modalities in AI agents
• Agent Framework Integration: Implement speech capabilities with LangChain/LangGraph, CrewAI, AutoGen, LlamaIndex, and OpenAI Assistants API

MLOps & Production Engineering

• Model Lifecycle: Implement comprehensive MLOps pipelines using MLflow, Weights & Biases, and automated CI/CD
• Multi-cloud Deployment: Deploy speech models across AWS Bedrock, Google Cloud AI, and Azure Cognitive Services
• Real-time Processing: Build WebSocket-based streaming audio systems handling 1000+ concurrent connections
• Production Monitoring: Implement WER tracking, latency monitoring, and multi-provider failover mechanisms

Research & Development

• Cutting-edge Research: Stay current with latest speech AI breakthroughs and implement novel architectures
• Performance Optimization: Optimize models for real-time inference using TensorRT, ONNX, and edge deployment
• Data Pipeline Engineering: Build scalable audio ingestion, preprocessing, and augmentation systems

Required Qualifications

Core Technical Skills (Must-Have)

Speech AI Models (3+ years experience):

Programming & Frameworks:

MLOps & Infrastructure (Essential)

MLOps Tools (2+ years):

Cloud & Production:

Preferred Qualifications

Advanced Specializations

• Multi-lingual Processing: Cross-lingual transfer learning, zero-shot adaptation
• Domain Expertise: Healthcare, legal, technical domain speech AI
• Edge AI: TensorRT, Core ML, ONNX optimization for mobile/edge deployment
• Research Background: Publications in ICASSP, INTERSPEECH, ICML, NeurIPS

Leadership & Education

• Team Leadership: Experience leading speech AI teams and technical initiatives
• Education: MS/PhD in Computer Science, Electrical Engineering, or related field
• Open Source: Contributions to speech AI libraries and frameworks

Technical Environment

Production Technology Stack

Core Technologies:

Production Models:

Infrastructure

• GPU Clusters: NVIDIA A100/H100 for model training
• Edge Deployment: NVIDIA Jetson, ARM-based targets
• Real-time Requirements: 300ms latency, 1000+ concurrent streams
• Enterprise Integration: Genesys AudioConnector, SIP protocol, telephony systems

Key Projects & Success Metrics

Primary Focus Areas

1. Next-gen S2S Systems: Amazon Nova Sonic, Azure OpenAI Realtime, Gemini Native Audio
2. Multi-cloud Integration: Unified APIs across AWS, Google Cloud, Azure
3. Conversational AI Agents: Low-latency speech-enabled customer service bots
4. Telecom Integration: Enterprise telephony and AudioConnector systems
5. Domain-specific Models: Medical, legal, technical vocabulary fine-tuning

Success Metrics

• Performance: 5% WER for domain-specific tasks
• Latency: 300ms end-to-end processing
• Reliability: 99.9% uptime for production services
• Scale: 1000+ concurrent speech streams