We expect you to:
— Have advanced knowledge in relevant areas of mathematics and statistics
— Have a working knowledge of various techniques, tricks and best practices for designing deep nets, hyperparameter optimization, visualization, interpretation, etc.
— Have a bunch of failure stories about the deep learning projects you’ve been involved in (and maybe even a couple of success stories)
— Have experience and good understanding of deep generative models (ideally models of audio, like WaveNet, SampleRNN, Tacotron, and MelNet)
Would be a plus:
— Knowledge of Digital Signal Processing theory
— Knowledge of speech processing
— Knowledge of CUDA / interest in developing custom CUDA kernels
— Experience deploying machine learning models
— Devops experience (Kubernetes, etc.)
We are looking for open-minded middle/senior engineers to join our team. We really enjoy the stuff we do. We are a little team of 6 people, and we have funding and market traction. The technical core is based in Kyiv.
Please peruse our job descriptions, and if you think you could fit into our team do not hesitate to contact us!
— Do real research with deep generative models of audio in a small, scientifically-minded team
— Freedom to try out ideas of your own
— There might be publication opportunities
We also offer stock options.
— Implement and maintain deep learning models in Tensorflow and PyTorch
— Train models, keep track of performance, and tune hyperparameters
— Proactively read relevant literature and generate ideas for model enhancements
— Help with deployment and ops as needed
We are a startup creating a system which lets anyone speak with anyone’s voice, focused on very high quality output and usability for demanding applications like TV and movies, call centers, and gaming. We have projects underway with one of top Hollywood studios and a major British broadcaster. We are in the Techstars startup accelerator.