Summary

Results-driven Machine Learning Engineer with over 5 years of experience designing, building, and deploying scalable end-to-end ML solutions in production cloud environments. Expertise in developing production-grade systems that handle millions of requests daily, including advanced NLP pipelines, decision support systems, and robust large-scale model deployment infrastructures. Specializes in microservice architecture (Java, Spring Boot) and MLOps best practices, effectively translating complex enterprise challenges into impactful, data-driven applications.

Education

• B.Tech in Computer Science and Engineering

  2020
  SASTRA Deemed to be University

  Courses: Data Structures, Algorithms, Database Management Systems, Artificial Intelligence, Object-Oriented Design

Work Experience

• Lead Data Scientist

  July 2025
  Freshworks

  • Directed transition of features to open-source LLaMA and Qwen models, utilizing quantization techniques and assessing output quality with MLflow's LLM-as-a-Judge framework.
  • Spearheading enhancements to the RCA product feature to support higher customer data volumes and improved anomaly detection throughput.
  • Architecting an organization-wide evaluation framework for agent-based AI features, standardizing quality measurement across agentic workflows
• Senior Data Scientist

  July 2022 - June 2025
  Freshworks

  • Engineered and implemented a production-scale Custom Intent Detection microservice, enabling customers to train models on their own data, overseeing 10,000+ live custom models handling approximately 1 million daily requests.
  • Designed and implemented an organization-wide MLOps framework covering model monitoring, feedback loops, and data and model version tracking to enhance operational efficiency
  • Built an Entity Extraction service to identify and extract structured entities from support tickets and live chat conversations.
  • Designed and implemented a Query-to-Graph agentic system, enabling customers to build analytical dashboards and conduct data-driven conversations using natural language queries
  • Developed and deployed a Root Cause Analysis (RCA) product feature leveraging Generative AI and data analysis techniques to proactively alert customer business leaders about anomalies in their key business metrics, along with AI-generated potential root causes.
• Data Scientist

  April 2021 - June 2022
  Freshworks

  • Developed and integrated a conversational AI model for small talk interactions within the chatbot framework, improving user experience and dialogue effectiveness.
  • Designed and deployed a production-grade Embedding service by quantizing the LaBSE model, building a high-performance inference layer, and deploying it for large-scale production use.
• Graduate Trainee - Data Science

  October 2020 - March 2021
  Freshworks

  • Implemented a Question-and-Answer (QnA) retrieval system and integrated it with the existing AI chatbot to improve response accuracy and coverage.
• Data Science Intern

  December 2019 - September 2020
  Freshworks

  • Enhanced the AI chatbot to incorporate communication channel-based context, enabling more relevant and personalized bot responses across different messaging channels.
  • Implemented Global Feedback Flows for the chatbot platform, enabling structured collection of user feedback to drive continuous improvement

Skills