AI Innovator

3 days ago

Mount Abu, Rajasthan, India beBeeSpeechEngineer Full time ₹ 1,50,00,000 - ₹ 2,01,00,000
Job Summary

We are seeking a skilled AI Engineer specializing in Speech and Voice Systems to lead the design and optimization of speech recognition, text-to-speech, and wake-word detection pipelines for a next-generation consumer AI product.

About the Role

This role focuses on delivering natural, low-latency voice interactions that work reliably on constrained hardware (edge devices) and scale seamlessly with cloud infrastructure. You will be responsible for developing and optimizing speech-to-text systems for low-latency recognition, implementing and enhancing text-to-speech systems, including multi-voice support and style variations, prototyping and refining wake-word detection, and integrating noise suppression, VAD, AGC, and audio normalization for robust performance.

Key Responsibilities:
  • Design and develop speech-to-text systems for real-time recognition.
  • Implement and enhance text-to-speech systems for high-quality output.
  • Develop and refine wake-word detection algorithms for accurate performance.
  • Optimize models for offline/CPU-first inference.
  • Design caching, streaming, and batching strategies for real-time performance.
  • Collaborate with backend engineers to expose APIs for integration into apps.
  • Monitor performance via observability dashboards.
Requirements:
  • 5+ years of professional experience in applied AI, with at least 3 years focused on speech technologies.
  • Proven experience building production-grade STT/TTS systems.
  • Strong knowledge of audio/DSP fundamentals: resampling, denoising, VAD, loudness normalization.
  • Proficiency in Python; experience with FastAPI/Docker for model serving.
  • Familiarity with wake-word frameworks and streaming audio integration.
  • Track record of delivering low-latency speech systems optimized for edge devices.
Nice to Have:
  • Experience with multilingual voice systems.
  • Familiarity with real-time streaming architectures.
  • Exposure to IoT/edge deployment.

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