• A Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field from leading research institutes.
• Strong working experience in building speech technologies like Automatic Speech Recognition (ASR), Multilingual Speech Recognition, Diarization, Language Model, Pronunciation Model, Audio classification.
• Hands-on experience in building Hybrid speech recognition systems like GMM-HMM, DNN-HMM
• Hands-on experience in building end-to-end speech recognition systems using the latest architectures like wav2vec2, HuBERT, Whisper, LAS.
• 2 years of hands-on experience in speech processing frameworks such as Kaldi, Espnet, Speechbrain, etc.
• Experience with machine learning and deep learning libraries such as Scikit Learn, TensorFlow, or PyTorch.
• Strong programming experience in languages like Python, C/C++, Shell scripting etc.
• Experience contributing to research communities, including publications at conferences and/or journals (a plus)

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