Apr 2024 – Jan 2025 · 9 mos · Hyderabad, Telangana, India

• Headed the global MLOps team, providing leadership and mentoring to team members, including onboarding new joiners and guiding them to success.
• Pioneered the development and organizational adoption of an in-house Chubb GPT API, leveraging Microsoft Azure’s OpenAI models to drive innovation across the company.
• Led the strategic migration from Azure 1.9 to Azure 2.0, collaborating with DevOps teams to design and implement new cloud infrastructure, cognitive resources, and updated network and security frameworks.
• Led the end-to-end deployment of over 30 projects into production environments, utilizing Docker, Azure Kubernetes Service (AKS), and Jenkins to ensure smooth and successful rollouts.

Mar 2022 – Mar 2024 · 2 yrs · Hyderabad, Telangana, India

• Achieved ~800 manual hours savings and ~$50K annual costs savings through creation of In-house MLOps Platform for ML/DL projects from ground up to bring down the deploying, monitoring and scaling of models time to less than 15 mins using Azure services like AKS, Azure Application Insights, Jenkins(CI/CD), Kubernetes and Docker.
• Worked on Pre-processing of Un-Structured Data with 11million records and implemented NLP Model from Hugging Face like Transformer Question-Answering (Roberta), Summarization (longformer-base-4096) and Doc-Classification(distibert-base-uncased) model and fine-tuned the pre-trained transformers Model for multiple ML/DL use-cases.
• Responsible for creating asynchronous API Wrapper using FastAPI framework, code refactoring, building of Docker images and deployment on Azure Kubernetes(AKS) for ML/DS use cases to facilitate smooth onboarding on platform.
• Rich stakeholder management experience, proficient in grasping the big picture, conceptualizing, developing & partnering closely with cross functional business leaders & teams.

Mar 2021 – Feb 2022 · 11 mos · Pune, Maharashtra, India

• Awarded twice with Star Award and Thumbs Up Awards within 8 months of the tenure for outstanding performance.
• Developed and managed data pipelines using Apache Airflow on AWS to orchestrate machine learning workflows.
• Integrated Airflow with various AWS services, including Lambda, S3, and DynamoDB, to streamline MLOps workflows and ensure reliable job execution and Implemented monitoring and alerting mechanisms in Airflow to ensure data and workflow accuracy and handle failure recovery.
• Created and managed AWS CloudFormation templates to automate infrastructure provisioning and ensure consistency across environments.
• Worked on DevOps environment for integrating test cases in Teams City (CI-CD tool) to automate validations for new builds and generating artifacts and HTML reports for passed and failed cases.
• Created a customizable dashboard for better visualization and monitoring of data metrics in Grafana for API’s Performance and server performance viz. CPU Usages, Disk Usages, Network Usages, etc. Designed Framework with the help of Grafana, Influx DB, JMeter, and telegraph.

Dec 2020 – Jan 2021 · 1 mo · Bangalore Urban, Karnataka, India

• Collected the data from National Family Health Index Survey regarding sanitation and water facilities for various states, cleaning the data and exploratory data analytics (EDA) and integrating the same into django restful API.
• Calculating the impact on Infant Mortality and Maternal Mortality due to poor sanitation, latrine facilities and water sources in India.
• Implemented the machine learning algorithms to find the sanitation risk for each of the PIN
• codes in a particular state and also analysis the chances of getting affected with other diseases on the basis of sanitation, latrine and water facilities.
• Assessing the risk and Calculating the impact on public health on the basis of Air Quality Index
• with the help of Machine Learning model.