# Kirthan Prakash > Software Engineer @ Zoox | MSDS @ TAMU | ex-MLE @ Quantiphi | NITK Location: San Mateo, California, United States Profile: https://flows.cv/kirthan I'm currently working as a Software Engineer at Zoox on the Planner Metrics team. I have a strong passion for leveraging Machine Learning, Deep Learning, and Data Science to solve real-world problems. ## Work Experience ### Software Engineer @ Zoox Jan 2025 – Present | Foster City, CA Autonomy Software Integration - Metrics Engineer - Building behavioral metrics and data pipelines to evaluate software system performance across a continuously evolving autonomy stack. - Building high-quality data miners to surface new and previously undetected behavioral issues in the software stack. - Developing and maintaining longitudinal VnV reporting frameworks to quantify progress and track system improvements over time. - Implemented automatic gating to detect behavioral regressions in PRs before integration. ### Graduate Teaching Assistant @ Texas A&M University Jan 2024 – Jan 2024 | College Station, Texas, United States - Graduate Teaching Assistant for STAT 624 Databases and Computational Tools for Big Data under Prof. Toryn Schafer in Spring 2024. - Assist students in utilizing GitHub for version control and collaborative development. - Support students with Docker to containerize applications for easy deployment. - Aid students in querying and managing relational databases effectively with PostgreSQL - Guide students in utilizing NoSQL databases for flexible data storage. - Help students leverage Python libraries for data analysis and visualization. - Assist in parallelizing computations with Dask for efficient data processing. ### AI Metrics Intern @ Zoox Jan 2024 – Jan 2024 | Foster City, California, United States - Refactored key comfort metrics from legacy to modern architecture built with Bazel, Protobuf, and PipeDream, using the Visitor Design Pattern, reducing computation costs by 10%. - Designed a predictive workflow for identifying false positive collisions, resulting in accelerated development cycles, reduced QA timelines, streamlined communication, and accelerated PR merges. ### Machine Learning Engineer @ Quantiphi Jan 2021 – Jan 2023 | Bangalore Urban, Karnataka, India 1. Managed MLOps for around 150 workflows, including ETL pipelines, Churn Propensity, Segmentation, Dormancy Winback, and Classification models, using Apache Airflow and AWS to target the weekly marketing campaigns. Handled the entire migration of the codebase along with 500 TB of data from IBM Netezza to AWS Redshift. 2. Built document processing workflows using AWS Cloud Services to classify, extract and store key information for the digitization of documents leveraging the power of deep learning for varied clients: - ML Lead for the project on extracting PII data from ophthalmic prescriptions. Deployed an ensemble model consisting of Detectron2, GraphTSR, and LayoutLMv3 models in the client environment, reducing the turnaround time by over 70% while maintaining high extraction accuracies. Built the entire backend re-training pipeline which reduced human effort time by 48 hours per week. - A core member of the ML team in building a solution to classify and extract confidential information from non-disclosure agreements for a global transport and logistics company. - Revamped and incorporated the LinearSVC and Elmo biLSTM models to assist the client in classifying the identity documents and extracting PII data from them. - Deployed an automated workflow, consisting of U2Net Segmentation and ARShadowGAN models, for cropping a car, adding a shadow to the cropped image, and placing it on a standard background, facilitating an automotive retailer-based company in reselling used cars. 3. Worked on enhancing the internal QDox platform by integrating PICK, GraphTSR, LayoutLM, LayoutXLM and LinearSVC models with the UI. Aided in optimizing the overall costs by replacing all Provisioned endpoints on the platform with Serverless endpoints. ### AI Intern @ Graphene Semiconductor Services Pvt Ltd. Jan 2020 – Jan 2021 | Bangalore Urban, Karnataka, India - Data tagging and pre-processing for the Sentiment Intensity models to detect customer emotions on various FMCG goods - Researched and deployed the GCP Sentiment Intensity Analysis model and Microsoft Azure Sentiment Analysis model in Microsoft Cognitive Services. Tested both models on the dataset to check which works best for our use case. - Finally automated the process to detect customer emotions leveraging a semisupervised learning approach consisting of state-of-the-art models and rule-based post-processing ### HR and Marketing Management Intern @ Arvind Goodhill Suits Manufacturing Pvt Ltd Jan 2019 – Jan 2019 | Bangalore Urban, Karnataka, India - Organizing Head for the sale held in Deloitte, Bangalore - Part of the organizing and planning team for sales held in JP Morgan, Morgan Stanley, and KPMG - Worked under the supervision of the Marketing Head and accompanied her in various client meetings. ### Data Intern @ Wadhwani Foundation Jan 2018 – Jan 2018 | Bangalore Urban, Karnataka, India - Organized a 10-day classroom program on entrepreneurship for professors from India, Latin America, South Africa, East Africa, Egypt, and Southeast Asia. - Organized and facilitated faculty training through Wadhwani Global University across universities in several countries. - Organized a regional entrepreneurship event. - Trained and worked with professors of premium institutes in India, the Philippines, and Uganda. ## Education ### Master of Science - MS in Data Science with CSE Track Texas A&M University ### Bachelor of Technology - BTech in Electrical and Electronics Engineering National Institute of Technology Karnataka ### Pre-University Course (11th and 12th) AECS Magnolia Maaruti Public School - India ### ICSE Bethany High School - India ## Contact & Social - LinkedIn: https://linkedin.com/in/kirthan-prakash --- Source: https://flows.cv/kirthan JSON Resume: https://flows.cv/kirthan/resume.json Last updated: 2026-04-11