About

Anchit Agarwal is a skilled and experienced software developer with expertise in machine learning and data engineering. Currently working at Zillow, he is responsible for developing distributed cloud services for AI and data platforms. Anchit has worked on Home Valuations ML pipelines, implemented distributed model training and serving on the cloud, and is currently developing a self-serve data platform built on the tenets of data mesh. At Zillow, Anchit is building a company-wide data platform following the tenets of data mesh to ingest, transform, and warehouse data. He is developing scalable modular solutions to ingest streaming records from numerous Zillow data sources and working with Airflow/dbt to provide common transformation modules. Anchit is also developing storage agnostic ingestion and transformation patterns. Anchit has previously worked on the AI Platform Model Training & Serving team and developed a seamless interface for customers to submit distributed PyTorch model training jobs on Kubeflow and Metaflow. He also built a custom serving interface for AIP customers to serve their models in a reliable, scalable manner with appropriate monitoring in place. Anchit has also worked on the Home Valuations team, commonly known as Zestimates, where he developed and maintained several modules in the Zestimates ML pipeline. He added data processing modules such as GeoETL that process the distance of each 110M houses from geographic features such as roads, water, etc. Anchit has also worked on adding a new deep neural network module to the Zestimates pipeline. Anchit holds a Master of Science (MS) degree in Computer Science from Arizona State University and an MSc (Tech) degree in Information Systems from BITS. He is proficient in various technologies, including Software Engineering, AI, ML, Data Engineering, Apache Airflow, Pytorch, and Neural Networks. With relevant experience of 5.86 years, Anchit is a highly skilled and dedicated software developer with a passion for developing innovative solutions and pushing boundaries in the field of machine learning and data engineering.