
AI Specialist
2 weeks ago
We are seeking an experienced engineer to design and optimize speech recognition, text-to-speech, and wake-word detection pipelines for our applications.
The role focuses on delivering natural, low-latency voice interactions that work reliably on constrained hardware (edge devices) and scale seamlessly with cloud infrastructure.
- Key Responsibilities:
- Create and optimize speech-to-text systems for real-time recognition
- Develop and enhance text-to-speech systems, including multi-voice support and style variations
- Prototype and refine wake-word detection and integrate noise suppression, VAD, AGC, and audio normalization for robust performance
- Apply model optimization techniques for offline/CPU-first inference
- Design caching, streaming, and batching strategies to meet performance targets
- Collaborate with engineers to expose APIs for integration into applications
- Monitor performance via observability dashboards
- Ensure privacy-first design: local-first processing with optional cloud fallback
- Qualifications:
- 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 (PyTorch); 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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