Apr 2024 – Mar 2026 · 1 yr 11 mos · Bengaluru · Hybrid

• Integrating Agentic capabilities and multi agentic capabilities to across products in LAM
• Worked on LLM, Multi-Model LLM based RAG application
• Developed and fine-tuned QLoRA models to enhance the efficiency and accuracy of Retrieval Augmented Generation (RAG)
• systems
• Led the setup and management of Azure Labelling projects, overseeing the entire lifecycle from initial data labeling to model
• deployment and operationalization
• Spearheaded the creation and validation of machine learning models for Inclusion and Stain classification, ensuring robust
• performance through thorough model validation and User Acceptance Testing (UAT).
• Conducted code reviews to ensure high standards in coding practices, maintainability, and adherence to security operations
• guidelines, Solved complex technical problems related to model deployment , scaling, and optimization.

Sep 2023 – Sep 2024 · 1 yr

Jan 2023 – Apr 2024 · 1 yr 3 mos

• Streamlined Data Processing with GCP: Led architecture and implementation of end-to-end data processing pipelines using Google Cloud Dataflow. Parallelized data ingestion, transformation, and storage with Apache Beam, achieving a remarkable 40% reduction in processing time.
• Scalable Data Lake on GCP: Conceptualized and deployed a scalable data lake on Google Cloud Storage. Utilized the Parquet file format to streamline data storage and retrieval, resulting in reduced data footprint and expedited query processing.
• Seamless Machine Learning Integration: Collaborated closely with Data Science teams, seamlessly integrating machine learning models into data pipelines. Leveraged Google Cloud ML Engine for model training, leading to a remarkable 25% boost in predictive accuracy.
• Real-time Insights with Streaming: Leveraged Apache Kafka and Google Pub/Sub for real-time data streaming, providing stakeholders with instantaneous insights for agile decision-making.
• Empowering GCP Mastery Across Teams: Facilitated knowledge transfer sessions, empowering cross-functional teams with GCP tools. Organized workshops on Dataflow, BigQuery, and ML Engine to democratize data insights and enhance agility.
• Automated Deployment Excellence: Established CI/CD practices using Google Cloud Build and Cloud Functions, streamlining deployment workflows and ensuring consistent code quality, accelerating development cycles.
• Optimized Data Processing with Dataproc: Orchestrated Apache Spark workflows on Google Cloud Dataproc, leveraging parallelized processing and scalability. Achieved a 20% reduction in data processing costs through dynamic cluster scaling.
• Visualizing Insights with Looker: Collaborated with stakeholders to design interactive Looker dashboards, empowering informed decision-making with comprehensive visualizations.

Oct 2021 – Feb 2023 · 1 yr 4 mos · Pune, Maharashtra, India

• Led a team that achieved 4.8 % revenue growth for the Marketing Analytics team of a US Healthcare client, leveraging AWS Redshift, Spark-powered advance SQL analysis, and ETL pipelines to analyze healthcare data set
• Enhanced operational efficiency by saving 30 hours/week through Visual Basic Application (VBA)-powered automated reports
• Developed and optimized SQL queries for patient segmentation, incorporating strategic indexing and query restructuring techniques, resulting in a 20% improvement in query performance
• Utilized machine learning algorithms for patient segmentation project
• Collaborated with the development team to reproduce and verify bug fixes, ensuring a 95% accuracy.

May 2021 – Oct 2021 · 5 mos

• writing complex SQL for data analysis and data profiling
• Worked very closely with business analysts, development teams and project managers for requirements and business rules
• Working in .NET framework and C# technology
• Hands on ETL development using any combination of Ab Initio, Ab Initio Express IT and Ab Initio Continues Flows in an agile development environment.

Apr 2020 – Jul 2020 · 3 mos · Hyderabad, Telangana, India

• under super vision of Dr Sai Sidhardh and Dr. Konda Reddy Mopuri(mentor)
• research areas : Deep Learning, Computer Vision and Machine learning and finite element simulations
• Depts associated : Artificial Intelligence and finite element simulations
• Laplace and Inverse Laplace transforms and their properties, and working the solutions Numerical Analysis and Computer programming of Euler's equation of motion for inviscid flow; Stream-lines, the path of a particle; Potential flow; , Cauchy's method of characteristics; Linear partial differential equations of the second order with constant coefficients, the canonical form

Jan 2018 – Jan 2019 · 1 yr

• Advanced Mathematics and Numerical Analysis