About the Role

We are seeking an experienced AI Engineer with deep expertise in voice technologies to lead the development and deployment of voice-first and conversational AI applications. This role involves working with speech recognition (ASR), text-to-speech (TTS), and natural language understanding (NLU) systems to power voice assistants, smart chatbots, and human-like voice interactions in enterprise environments.

Key Responsibilities

Develop and optimize advanced speech-to-text (ASR) and text-to-speech (TTS) systems for production use.
Build and integrate voice-enabled applications, chatbots, and AI-driven virtual assistants.
Design and implement NLP/NLU models to capture user intent, context, and sentiment.
Integrate voice technologies into enterprise platforms such as ERP, CRM, contact centers, and mobile/web apps.
Work with leading cloud-based AI/voice services:
- Google Cloud Speech-to-Text / Dialogflow
- Amazon Lex / Polly
- Azure Cognitive Services for Speech
Use open-source frameworks like DeepSpeech, Whisper, Kaldi, Rasa, and Dialogflow.
Optimize applications for low-latency, accuracy, and multilingual support.
Collaborate with cross-functional teams (AI/ML, product, design, UX, engineering) to create scalable, user-centric solutions.
Research and integrate emerging Generative AI technologies for voice (e.g., voice cloning, emotion modeling, real-time synthesis).

Required Skills & Experience

Proven experience (4+ years) as an AI/ML Engineer with a strong focus on voice-based AI applications.
Expertise in:
- Speech Recognition (STT/ASR)
- Text-to-Speech (TTS)
- NLP/NLU for conversational AI
Strong programming skills in Python, with experience in TensorFlow, PyTorch, or similar ML libraries.
Hands-on experience with one or more of the following:
- DeepSpeech, Whisper, Kaldi, Mozilla TTS
- Dialogflow, Rasa, Amazon Lex, Microsoft LUIS
Experience with cloud AI services: AWS, GCP, Azure (voice-related APIs and tools).
Solid understanding of audio signal processing and real-time voice system optimization.
Ability to design scalable, resilient architectures for enterprise-grade voice solutions.

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