• University degree in Speech/Computer Science/Engineering (Master/PhD)
• Experience with GMM-HMM and DNN based models.
• Experience with Linux environments and scripting languages (Python, Bash).
• Experience with Kaldi speech recognition toolkit.
• Experience with ASR pipelines and Weighted Finite-State Transducers (WFSTs)
• Good knowledge of advanced ASR concepts (e.g. speaker adaptation, diarization and Vocal Tract Length Normalization).
You like a challenge and are a pleasant person to work with.
Due to the distributed nature of our team, being a self starter is important.
Also communication skills and proficient English.
Having an affinity with our mission in with improving education and healthcare is important. We’d like to work with other driven and enthusiastic people.