I help develop the core deep learning production inference system that powers our high performance, high accuracy ASR models. This involves:

* Low-level tuning of algorithms to maximize throughput and minimize memory footprint

* Systems-level work to optimize data flows in an HPC context

* Implementing cutting-edge deep learning models so that they can be put into production

* Benchmarking deep learning systems as well as testing them for accuracy

* Troubleshooting production issues to maintain high uptime

Full stack development for machine learning platform.

I support deep learning research efforts at Deepgram through the development and maintenance of critical hardware and software infrastructure. Additionally, I help develop some of our SaaS products. Below are some of the projects I have worked on:

• Developed optimized GPU versions of key proprietary algorithms using CUDA

• Built and managed GPU cluster used for training Deep Learning ASR models

• Developed custom Python modules (written in C) to perform fast GPU-to-GPU data transfers using OpenMPI during multi-GPU deep neural network training in Tensorflow

• Wrote web application back-ends (SaaS product, system monitoring, etc.) using Python with Tornado and PostgreSQL and front-ends using Vue.js

• Implemented custom Allreduce methods using OpenMPI primitives to optimize deep neural network model training

• Developed Python data augmentation tools for audio data used in automatic speech recognition training tasks

• Implemented novel audio search algorithm for client to maximize speech search performance. Delivered C++ code and Python wrapper.

• Developed educational technology Android application. Python/Tornado and MySQL were used for the back-end. AngularJS used for the front-end of a companion web application.

• Developed a web-based system for synchronization and administration of tasks across a network of embedded systems for an art installation