Data Scientist
4 weeks ago
About the Role:We are seeking a highly experienced Voice AI /ML Engineer to lead the design and deployment of real-time voice intelligence systems. This role focuses on ASR, TTS, speaker diarization, wake word detection, and building production-grade modular audio processing pipelines to power next-generation contact center solutions, intelligent voice agents, and telecom-grade audio systems.You will work at the intersection of deep learning, streaming infrastructure, and speech/NLP technology, creating scalable, low-latency systems across diverse audio formats and real-world applications.Key Responsibilities:Voice & Audio Intelligence:- Build, fine-tune, and deploy ASR models (e.g., Whisper, wav2vec2.0, Conformer) for real-time transcription. - Develop and finetune high-quality TTS systems using VITS, Tacotron, FastSpeech for lifelike voice generation and cloning. - Implement speaker diarization for segmenting and identifying speakers in multi-party conversations using embeddings (x-vectors/d-vectors) and clustering (AHC, VBx, spectral clustering). - Design robust wake word detection models with ultra-low latency and high accuracy in noisy conditions.Real-Time Audio Streaming & Voice Agent Infrastructure:- Architect bi-directional real-time audio streaming pipelines using WebSocket, gRPC, Twilio Media Streams, or WebRTC. - Integrate voice AI models into live voice agent solutions, IVR automation, and AI contact center platforms. - Optimize for latency, concurrency, and continuous audio streaming with context buffering and voice activity detection (VAD). - Build scalable microservices to process, decode, encode, and stream audio across common codecs (e.g., PCM, Opus, μ-law, AAC, MP3) and containers (e.g., WAV, MP4).Deep Learning & NLP Architecture:- Utilize transformers, encoder-decoder models, GANs, VAEs, and diffusion models, for speech and language tasks. - Implement end-to-end pipelines including text normalization, G2P mapping, NLP intent extraction, and emotion/prosody control. - Fine-tune pre-trained language models for integration with voice-based user interfaces.Modular System Development:- Build reusable, plug-and-play modules for ASR, TTS, diarization, codecs, streaming inference, and data augmentation. - Design APIs and interfaces for orchestrating voice tasks across multi-stage pipelines with format conversions and buffering. - Develop performance benchmarks and optimize for CPU/GPU, memory footprint, and real-time constraints.Engineering & Deployment:- Writing robust, modular, and efficient Python code - Experience with Docker, Kubernetes, cloud deployment (AWS, Azure, GCP) - Optimize models for real-time inference using ONNX, TorchScript, and CUDA, including quantization, context-aware inference, model caching. - On device voice model deployment.Why join us?- Impactful Work: Play a pivotal role in safeguarding Tanla's assets, data, and reputation in the industry. - Tremendous Growth Opportunities: Be part of a rapidly growing company in the telecom and CPaaS space, with opportunities for professional development. - Innovative Environment: Work alongside a world-class team in a challenging and fun environment, where innovation is celebrated.Tanla is an equal opportunity employer. We champion diversity and are committed to creating an inclusive environment for all employees.
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