Position: Deep Learning Research Engineer
Company: Data Science UA
Experience required: 2y
English level: upper

Benefits:
● 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
● Office in the center

Duties:
● Implement and maintain deep learning models in 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 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 some success stories)
● Have a good understanding of deep generative models. You may work on autoregressive models, GANs, VAEs, or flow-based models.

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.)