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)
