Ajay Krishnan

I am a Machine Learning Engineer with interests in ML and Systems. I've built ML applications to solve problems ranging from Fashion and Retail to Climate Change. I’ve dealt with Petabyte Scale data and built reliable and resilient backend systems. I excel at swiftly devising solutions to diverse challenges all over the board, with a holistic approach that encompasses all aspects of a product. This makes me an ideal fit for teams dedicated to product development, prototyping, and efficient delivery. I received the Exceptional Contributor Award from NASA IMPACT and the IET E&T Innovation award for my work on Worldview Search - a pipeline currently deployed in NASA that made the process of data curation across Petabyte Scale data 10x Faster at almost free of cost! I also worked on Representation Learning research with NASA Frontier Development Lab and A*STAR Institute of Infocomm Research where I focused on building tools for interpretability and experimental benchmarks to demystify representation embeddings for Semi-Supervised Learning. I also like giving presentations and have given guest talks on ML at UC Berkeley, NASA FDL, George Mason University, Swiss Cognitive AI, and Vellore Institute of Technology. Currently, I work as an MLE at Mad Street Den, where I work on improving inference systems, Intelligent Document Processing, and maintenance of systems through disaster recovery plans to prevent data loss. When I'm not involved with tech, I like working with music. I handle promotion strategies, concert curation, and artist management.