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AI/ML Engineering @ Workday · HCM Product | Interested in reliable LLM systems in production
I like solving hard problems that actually ship. Currently at Workday, building ML and LLM-powered features into the HCM product suite used by thousands of enterprises. Before that, [24]7.ai, working on conversational AI and NLP. I've co-founded startups, won a few hackathons (most recently the Google Cloud Next AI Arena), taught deep learning at San Jose State, and shipped systems that real people use. Patents in NLP. Mostly interested in where LLM systems break in production - retrieval, agent reliability, evaluation - and what it takes to make AI genuinely useful inside real products.
San José State University
Master’s Degree, Computer Software Engineering
January 1, 2016 – January 1, 2017
Chaitanya Bharathi Institute Of Technology
Bachelor's degree in Information Technology, Information Technology
January 1, 2011 – January 1, 2015
Workday
Senior Machine Learning Engineer
September 1, 2024 – Present
Workday
Software Engineer
September 1, 2022 – October 1, 2025
[24]7.ai
Senior Software Engineer
March 1, 2020 – September 1, 2022
[24]7.ai
Software Engineer
June 1, 2018 – March 1, 2020
Deary LLC
Software Developer
May 1, 2018 – June 1, 2018
San Francisco Bay Area
SmartEar, Inc.
Software Engineer
March 1, 2018 – May 1, 2018
San Francisco Bay Area
San Jose State University
Graduate Teaching Assistant - Deep Learning
September 1, 2017 – December 1, 2017
San Jose
Deary LLC
Software Developer
April 1, 2017 – August 1, 2017
San Jose
Learnasky
Founder
March 1, 2012 – December 1, 2015
Travel app
August 1, 2017 – Present
★ An amazing project that changes the way people do air-shopping. ★ Project being incubated by IATA (International Air Transport Association) -Signed NDA
Smart email management system
May 1, 2017 – June 1, 2017
★ Developed a classification algorithm using Machine Learning, that can classify my emails into various categories like (email from a professor, a friend, a doctor, spam email, promotional email, etc.). ★ Used Natural Language Processing to extract information and features from the text. Concepts like NER (Named Entity Classification), Chunking, etc. were used. ★ Implemented the front end in Alexa where the user can ask if he has a new email and gets a reply back with the details if there is a new email. ★ Built a REST API in Node.js, Express Framework that accesses my emails using Gmail API (used OAuth 2.0 to access the API). ★ Building (now) a smart response system that replies to emails automatically by understanding the context using advanced Natural Language Processing and Deep Learning concepts. ★ Tech: Python 3.5, Flask, Sklearn, numpy, joblib, JSGF, NLTK (Natural Language Toolkit), Deep Learning, etc. A part of the demo: https://youtu.be/jLMUN6znkm4
Chatbot that helps students know information about a lecture
April 1, 2017 – May 1, 2017
★ Developed a classification algorithm using Machine Learning, that can classify student questions into different classes. Students can ask anything about the class like class timing, about the lecturer, syllabus, exams, etc. ★ Used JSGFs to generate the dataset by writing semantic rules, Natural Language Processing to extract features from the text, word2vec to convert the text to vectors, etc. ★ Tech: Python 3.5, Flask, Sklearn, numpy, joblib, JSGF, NLTK (Natural Language Toolkit). Demo: https://youtu.be/OV3YaMNqI_k
Virtualization of mobile sensors in the cloud - tracking animal movements
October 1, 2016 – December 1, 2016
★ Implemented virtualization of mobile sensors and built a multi-tenant, scalable and fault-tolerant cloud application in Node.js. Developed dashboards for users to visualize the sensor data. ★ Developed the app as a subscription-based model where the user can subscribe and unsubscribe to the sensors and get charged for the usage accordingly (pay as you use model). ★ Deployed the application on various cloud platforms and infrastructures to understand the difference. ★ Tech: Node.js, Express Framework, Angular.js, JQuery, Ajax, JavaScript, HTML5, CSS, GoogleMaps API, WebSockets, MySQL, Heroku, AWS, etc. # Demo: https://youtu.be/UZfjmu2Qmco
Library Management using Spring Framework
September 1, 2016 – October 1, 2016
★ Built a Library Management application with a user and a Librarian module. A user can borrow, extend, return and be added to waiting list for a book. A Librarian can add, edit and delete books. A user will be fined per day if the book is not returned on time. ★ Built using concepts of Spring like Dependency Injection, AOP, MVC, ORM, and transactions. ★ Implemented Transaction Management with JDBC and Persistence with JPA ★ Hosted in AWS EC2 Tech: Java, HTML5, CSS, Spring, etc. Demo: https://www.youtube.com/watch?v=yFDAXmuUYt8&feature=youtu.be
Assisting Seniors with Alexa
August 1, 2016 – Present
★ Developed an app on Alexa that assists seniors. ★ The project is now being built as a startup by MIT MBA graduates. Signed NDA. ★ Tech: Alexa skill development, Natural Language Processing, Machine Learning, Lambda, Node.JS, HTML5, QuickBooks APIs, CSS3, Ajax, Heroku, Express Framework etc.
Prototype of Amazon-Fresh
March 1, 2016 – May 1, 2016
★ Developed a prototype of Amazonfresh where farmers can register and post their products, customers can buy the products and drivers can collect the products and deliver it to the customers. ★ Implemented using MEAN stack. ★ Hosted on Heroku and Amazon AWS. ★ Tested the application for performance using Junit and improved the efficiency and speed of the application by using strategies like custom connection pooling for database access, caching, message queue and some changes in the front-end. ★ Tech: Node.js, MySQL, MongoDB, Angular js, Express Framework, Mocha, Jmeter, REST, HTML, CSS, Javascript, Jquery, Ajax, RabbitMQ, Redis cache, etc.
Personality analysis from tweets
February 1, 2016 – March 1, 2016
★ Developed a web application that analyses personality of a person from his tweets. The user needs to give a twitter handle as an input to the application. ★ Hosted on IBM Bluemix. ★ Tech: Node.js, Angular js, HTML, CSS, Javascript, IBM’s Personality analysis API, REST APIs of Twitter.
Prototype of Twitter
February 1, 2016 – March 1, 2016
★ Developed a prototype of Twitter with functionalities like posting a tweet, following/unfollowing people, retweeting, deleting a tweet, etc. ★ Used MEAN stack. ★ Hosted the application on Heroku. Used Amazon RDS(Relational Database Services) for MySQL and AWS EC2 for MongoDB ★ Tested the application for performance using Junit and improved the efficiency and speed of the application by using strategies like custom connection pooling for database access. ★ Tech: Node.js, MySQL, MongoDB, Angular js, Express Framework, Mocha, Jmeter, REST, HTML, CSS, Javascript, Jquery, Ajax, etc.
Sentiment analyzer using NLP
February 1, 2015 – April 1, 2015
# Built a standalone sentiment analyzer application that analyzes sentiment from big text paragraphs or sentences using Natural Language Processing. # Used Tkinter, NLTK (Tokenizing, stop word removal, stemming, etc.) # Developed an algorithm that counts the number of positive and negative words in the given text and scores each word by picking them from a custom built dictionary (contains words and their scores). The final sentiment is then calculated. # Also handled text that has negative contractions like (don’t, aren’t, can’t, etc.) # Tech: Python 2.7, Tkinter, NLTK(Natural Language Toolkit)
Learnasky
February 1, 2012 – November 1, 2015
★ Developed a web platform for students, teachers, and institutes. Worked in a complete real-time startup environment. ★ Built customized dashboards for teachers to give assignments and evaluate online. Lead a team of 15 members.
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for an innovative and fast-paced environment, evidenced by their involvement in startups (Learnasky, Deary LLC, SmartEar, Inc.), leading hackathon projects, and filing multiple patents. Their continuous engagement with cutting-edge technologies like Gen AI, LLMs, and Deep Learning shows a commitment to staying current and driving innovation. The breadth of projects, from chatbots to email management and sensor virtualization, indicates a versatile and curious mindset.
Soft Skills & Operational Fit
The candidate's project descriptions highlight initiative, problem-solving, and leadership (e.g., leading a team of 15, conceptualizing and leading a Gen AI project, winning a hackathon). The experience as a Graduate Teaching Assistant also suggests strong communication and mentorship abilities. The diverse project portfolio indicates adaptability and a proactive approach to learning and applying new technologies.