Speech Architect - Machine Learning Model Acidaes Solution

5.0 - 9.0 years

0 Lacs

noida, uttar pradesh

On-site

As a Speech Architect, you will lead the development of cutting-edge speech recognition and processing systems, focusing on complex tasks such as speaker diarization, automatic speech recognition (ASR), Sentiment/Emotion recognition, and transcription. You will guide a team of engineers and collaborate closely with other departments to deliver high-impact solutions. Lead and mentor a team of speech engineers, providing technical guidance and ensuring the successful delivery of projects. Architect and design end-to-end speech processing pipelines, from data acquisition to model deployment, ensuring systems are scalable, efficient, and maintainable. Develop and implement advanced machine learning models for speech recognition, speaker diarization, and related tasks using techniques such as deep learning, transfer learning, and ensemble methods. Conduct research to explore new methodologies and tools in the field of speech processing, publish findings, and present at industry conferences. Continuously monitor and optimize system performance, focusing on accuracy, latency, and resource utilization. Work closely with product management, data science, and software engineering teams to define project requirements and deliver innovative solutions. Engage with customers to understand their needs and provide tailored speech solutions, assisting in troubleshooting and optimizing deployed systems. Establish and enforce best practices for code quality, documentation, and model management within the team. Bachelor's, Master's, or Ph.D. in Computer Science, Electrical Engineering, or a related field. 5+ years of experience in speech processing, machine learning, and model deployment, with demonstrated expertise in leading projects and teams. In-depth knowledge of speech processing frameworks like Wave2vec, Kaldi, HTK, DeepSpeech, and Whisper. Experience with NLP, STT, Speech to Speech LLMs, and frameworks like Nvidia NEMO, PyAnnote. Proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or Keras. Experience with large-scale ASR systems, speaker recognition, and diarization algorithms. Strong understanding of neural networks, sequence-to-sequence models, transformers, and attention mechanisms. Familiarity with NLP techniques and their integration with speech systems. Expertise in deploying models on cloud platforms and optimizing for real-time applications. Excellent leadership and project management skills. Strong communication skills and ability to work cross-functionally. Experience with low-latency streaming ASR systems. Knowledge of speech synthesis, STT (Speech-to-Text), and TTS (Text-to-Speech) systems. Experience in multilingual and low-resource speech processing.,

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