About

Virendra Meena is an experienced Machine Learning Engineer with over 10 years of relevant experience in building production-grade recommendation systems powered by machine learning. He is proficient in a wide range of technologies and tools, including the Spark stack, ML frameworks such as TensorFlow and scikit-learn, relational and NoSQL databases, streaming stack, machine learning toolset, programming and scripting languages, development notebooks and IDE, workflow scheduler, CI/CD and Artifactory, infrastructure as code, and container orchestration. Currently, Virendra is working as a Senior Machine Learning Engineer at Grab, where he is responsible for designing and developing forecasting services for food signals prediction and anomaly detection. He has also built a generic Flink operator to consume signals from Kafka topics and ingress to time-series DB. Virendra has also worked on building a promotion optimization ML-based food promos recommendation system, where he designed and implemented end-to-end ML workflows using Kubeflow pipeline SDK. Prior to Grab, Virendra worked as a Senior Software Engineer at Grab, where he designed, implemented, and rolled out the cloud-based commission service handling all drivers/merchants commission transactions across all businesses. He also worked on building a driver state manager service, a distributed backend service that tracks drivers’ online status over a trip life-cycle, location, booking details, taxi-types, preferences, and other useful metadata. Before joining Grab, Virendra worked as a Software Application Developer Analyst II at Citi, where he delivered time-to-market technology solutions for APAC Equities Trading Business in Global Market Access field. He has expertise in exchange knowledge, technologies such as C++, Java, and exchange protocols such as OMX/FIX/Binary, Vella(SRLab), 29West UME, Tibco EMS, Shell scripting, and Latex. Virendra holds a Master of Technology (M.Tech.) degree in Computer Science and a Bachelor of Technology (B.Tech.) degree in Computer Science from the Indian Institute of Technology, Kanpur. He also holds a degree from Maa Bharti Vidya Bhawan, Kota, Rajasthan. Virendra's tech stack includes ML, recommendation systems, AWS, Spark, Kafka, Scikit, Kubernetes, TensorFlow, SQL, Jupyter, XGBoost, Databricks, Terraform, Apache Airflow, CI/CD, Redis, Docker, MySQL, NoSQL, MongoDB, Jenkins, infra, software engineering,