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What you’ll be doing:
Train Speech Recognition (Acoustic, Language, Punctuation), Speech-to-text translation (AST), and Speech-to-speech (S2S) translation models.
Develop and maintain speech processing blocks and tools (alignment, segmentation, normalization etc.)
Improve processes for speech data processing, augmentation, filtering & Training sets preparation.
Measure and benchmark model performance.
Gather knowhow on speech datasets for training & evaluation.
Collaborate with various teams on new product features and improvements of existing products.
Help innovate, identify problems, recommend solutions and perform triage in a collaborative team environment.
Lead and mentor junior team members
What we need to see:
Master’s degree (or equivalent experience) or PhD in Computer Science, Electrical Engineering, Artificial Intelligence, or Applied Math with 5+ years of experience.
Excellent programming skills in Python, Strong fundamentals in Programming, optimizations and Software design.
Hands-on experience on Speech Technologies like Automatic Speech Recognition, Speech Command detection, Text to Speech, Speaker Recognition and Identification, speaker diarization, Noise robustness Techniques, Voice activity detection, End of utterance detection etc.
Strong knowledge of RNN-T, CTC, and transformer decoders.
Strong knowledge of ML/DL techniques, algorithms and tools with exposure to CNN, RNN (LSTM), Transformers.
Know-how of Deep learning applications to Speech and NLP
Experience with leading efforts and/or teams developing Speech AI products.
Exposure to basic speech digital signal processing and feature extraction techniques like FFT, MFCC, Mel Spectrogram, etc.
General background around version control and code review tools like Git, Gerrit, Gitlab.
Strong collaborative and interpersonal skills, specifically a proven ability to effectively guide and influence within a dynamic matrix environment.
Ways to stand out from the crowd:
Experience developing end-to-end and unified speech recognition and translation systems for multiple languages
Strong C++ programming skills.
Familiarity with GPU based technologies like CUDA, CuDNN and TensorRT
Background with Dockers and Kubernetes
Background with deploying machine learning models on data center, cloud, and embedded systems
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