Deep Learning Researcher - Language Modeling (Speech Recognition) (Remote)
If you're interested in applying to this position, please fill out the application here: https://forms.gle/96Rj1dtKYrmNdcVw5
\nAbout AssemblyAI
\nAt AssemblyAI, we use State-of-the-Art Deep Learning to build the #1 most accurate Speech-to-Text API for developers. We're backed by leading investors in Silicon Valley like Y Combinator, John and Patrick Collison (Stripe), Nat Friedman (GitHub), and Daniel Gross.
\nCustomers use our API to transcribe phone calls, meetings, videos, podcasts, and other types of media. Our accurate transcripts are used to power features like visual voicemail, call analytics, closed captioning, meeting summaries, and a slew of other features.
\nWe deploy our Deep Learning models into production to process millions of API requests per day.
\nAbout the Role
\nWe are growing rapidly and looking for an experienced Deep Learning Engineer to join our Speech Recognition Team, with a focus on Language Modeling. We're a small, creative, and democratic team interested in pushing the state of the art forward. You'll be leading the efforts on things like:
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- Training and improving the perplexity of N-Gram Language Models \n
- Coordinating and standardizing a data pipeline for several TBs of training data \n
- Researching and implementing Neural Language Models using state of the art approaches \n
- Digging into the beam search decoding algorithms, where the Language Models meet the Acoustic Models in modern ASR pipelines \n
- Researching and implementing Language Model Rescoring techniques into the ASR pipeline \n
Qualifications
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- 3-5+ years of experience with Python and C++ \n
- Experience with Deep Learning frameworks like PyTorch and TensorFlow \n
- Experience with Language Modeling toolkits like SRILM and KenLM \n
- Several years of experience training and building Language Models \n
- Some experience with modern Deep Learning based ASR systems (CTC, LAS, RNNTs) \n
- Ability to work independently and on a small team \n
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