Developed and deployed a large-scale ML-based monitoring and alerting system for a process execution graph (3M+ nodes), addressing use cases such as batch anomaly detection, forecasting, and ETA prediction, utilizing Apache Spark, HDFS, and Python.Created and implemented an unsupervised text clustering model with re-training capabilities for regex mining on alert notifications, trade exceptions, and system logs. A white paper was published on the same.Experimented with LLM-based chatbots for support ticket resolution, leveraging Confluence data and automating workflow generation using retrieval-augmented generation (RAG).Managed on-prem and cloud infrastructure using Infrastructure as Code (IaC) with Terraform. Led the RHEL7 upgrade and migration of 100+ servers, and migrated credentials from the on-prem Vault to HashiCorp Vault.

Led strategic initiatives at Vatanukool, optimizing inventory management and streamlining marketing efforts.Spearheaded the development of vatanukool.com using WordPress and WooCommerce.Utilized customer behavior analysis and market insights to enhance supply chain operations, leveraging tools like Google Analytics and Meta Business Suite.

Built lead generation pipelines that processed and enriched data from multiple sources, exporting 3M+ leads per month.Developed APIs for on-demand bulk lead exports, handling up to 50K leads per request and facilitating integration with customer CRM systems for seamless delivery.Implemented advanced lead filtering (ex. city, profession, experience, role, intent, etc.), enabling tailored lead generation that contributed to a 30% increase in repeat customer purchases.

Developed an LLM-based platform that optimized email productivity, reducing emailing time by 70% and saving users 20+ hours monthly through automation and SEO-optimized content.Led a team of 10 in delivering SaaS solutions to streamline email workflows, utilizing expertise in AWS and digital marketing.Demonstrated leadership in cross-functional team collaboration and innovative use of LLM’s to enhance user experience.

Led a team at the CoE-CNDS Lab, VJTI, to develop a real-time DeepFake detection solution using video vision transformers for spatio-temporal feature extraction.Published the research paper "Realtime Deepfake Detection Using Video Vision Transformer" at the 2022 IEEE Bombay Section Signature Conference (IBSSC), addressing critical challenges posed by deep fakes.Developed a user-friendly web application for video authentication and live meeting verification to enhance digital trust.Research Paper: https://ieeexplore.ieee.org/document/10037344

Developed an alert management solution at Goldman Sachs, automating the classification of 100K monthly alerts with 98% accuracy using NLP techniques.Created four resolution workflows, saving 120 hours per month in manual processing.Implemented trend detection analytics, delivering actionable insights for resource optimization in the SPARC team.

During my internship at AIRPIX, a Mumbai-based aerial systems startup, I played a key role in developing a Large-Scale and Real-Time Face Recognition System. Leveraging my expertise in AI, ML, and object detection, I led the design and implementation of this advanced system, which has the remarkable capability to identify over 10 thousand distinct individuals in real-time. This experience allowed me to push the boundaries of face recognition technology and showcase my technical skills in a practical setting.Working at AIRPIX provided invaluable insights into the practical application of AI and ML within the drone industry. Throughout the internship, I actively contributed to AIRPIX's mission of providing data processing and analytics solutions derived from drones. This experience not only enhanced my technical abilities but also reinforced my passion for AI, ML, and object detection. I am proud to have been part of a dynamic team that is at the forefront of revolutionizing the aerial systems industry with cutting-edge technologies.

As a Software Engineering Intern at JPMorgan Chase & Co., my role was to develop a robust data analysis and visualization system in the financial domain. During the two-month virtual experience, I designed and implemented an interface with a stock price data feed using Python. Leveraging the Perspective web application framework, I enhanced data visualization capabilities to align with JP Morgan Chase's model.Additionally, I created dynamic charts for the Trader's dashboard, enabling informed investment strategies based on real-time market data. This experience highlighted my expertise in software engineering, data analysis, and financial modeling. Collaborating with professionals, I gained valuable insights into the financial technology sector while delivering impactful results. My internship at JPMorgan Chase & Co. solidified my passion for software engineering and deepened my understanding of technology's role in finance.