Data Scientist

3 days ago

hyderabad district, India Tanla Platforms Limited Full time

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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