Deep Learning Researcher Speech Recognition vacancy at AssemblyAI

At 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.

Customers use our API to transcribe phone calls, meetings, videos, podcasts, and other types of media. Our accurate trans are used to power features like visual voicemail, call analytics, closed captioning, meeting summaries, and a slew of other features.

We deploy our Deep Learning models into production to process millions of API requests per day.

Responsibilities

Work with large scale datasets to research and train Deep Learning models for Speech Recognition
Conduct research and experiments in order to improve accuracy of Deep Learning ASR pipelines like CTC and RNN-Ts
Dig into weaknesses and failure points of our current ASR models, in order to identify further areas for improvement
Work with the broader Speech Recognition Team to publish papers on novel findings
Continually push the State of the Art in Speech Recognition to get to human level performance

Requirements

4+ years of experience with Python and C++
3+ years of experience with modern Deep Learning based ASR systems (CTC, LAS, RNNTs)
3+ years of experience training distributed deep learning models on GPUs
2+ years of experience with Deep Learning frameworks like PyTorch and TensorFlow