We're a Y Combinator (S17) backed deep learning company, building customizable speech-to-text solutions for companies working with voice data.
Using state of the art deep learning techniques, we train custom models for customers that are a perfect fit for their data (recording quality, noise, accent, etc), and more accurate than any other generic API/solution.
We're looking to bring on another deep learning engineer to work on things like:
- research and implement new papers to improve our model's accuracy, training speed, and compute footprint
- research and implement novel techniques using GANs to aid in data augmentation and normalization
- build new ML features like speaker detection
- help plan our deep learning strategy
We're super early (1.5 years old), so, depending on what you're looking for, this could be a great opportunity to help build a company from scratch with a lot of equity and a decent salary (we raised $1.2M last fall), while also being able to work on cutting-edge deep learning problems every day.
We don't care if you don't have a traditional Computer Science or Machine Learning background, self-taught engineers are more than welcome! What's more important is that you have a few projects/code to show us.
Our office is in San Francisco, but we are ok with remote team members!
If you're interested in learning more about our company and this role, please email us at jobs@assemblyai.com.