Ramesh Chowdary Email & Phone Number

College Station, Tx, Us

Texas, United States

Texas, United States

Liaised with cross-functional teams to gather requirements and define project goals for machine learning model serving and deployment. Executed benchmark event simulations to evaluate system performance through the variable number of customers interacting with deployed models. Conducted a comprehensive comparison between normal model serving and zero-copy deployment, highlighting the superior efficiency of zero-copy approach using deep learning models. Additionally, integrated sentiment analysis models like BERT models, and ChatGPT from OpenAI's GPT API for advanced AI-driven insights.• Accomplished remarkable scalability with zero-copy deployment, handling up to 170 chat sessions simultaneously with minimal timeouts, showcasing 5x scalability without any tuning and reducing infrastructure costs.• Maximized software delivery and deployment efficiency through the comprehensive execution of MLOps and DevOps practices, inclusive of ETL data pipelines and Docker for seamless containerization.• Enhanced operational efficiency significantly by developing monitoring and logging solutions for model serving with Grafana, Prometheus, and Azure ML.• Achieved efficient zero-copy serving of BERT language models by capitalizing Ray’s distributed computing functionality.• Increased scalability by employing Databricks, facilitating training and fine-tuning of NLP models on extensive datasets.• Reduced latency in high-performance model serving by deploying multiple clusters of GPU-accelerated VMs (Tesla T4).

Buffalo, New York, United States

Covid-19 Death Rate Prediction Service:• Enhanced data quality and relevance by conducting in-depth analysis and organization of raw Covid-19 data,implementing data cleaning, imputation, data wrangling, analytics, and feature elimination/extraction techniques.• Revealed significant patterns in extensive COVID-19 datasets through the effective utilization of statistical andexploratory data analysis for data preparation and predictive modeling.• Improved data comprehension by creating visually striking dashboards and reports with Tableau, elucidating global death rate patterns.• Optimized model performance by evaluating the accuracies of various regression models such as Linear, Logistic Regression, Decision Tree, Random Forest, and Time Series Analysis, to identify the most effective modeling approach.Machine Learning-Driven Analysis of US Commodity Trade Logistics• Streamlined US transborder trade logistics cost prediction by designing and formatting a comprehensive database with15 years of Historical data, identifying crucial predictors in the process for Analysis.• Amplified model accuracy to up to 94% by employing statistical modeling techniques and SVM-based approaches.• Fortified transportation cost by assisting in data engineering tasks, such as validation and compilation.• Facilitated key findings presentation by utilizing Tableau and MS SQL Server software for data visualization.• Augmented decision-making processes by conducting statistical modeling and data analysis on various parameters

Hyderabad, Telangana, India

Streamlined project management and team coordination by diligently updating the Jira board with task assignments and their status at the close of each day. Directed end-to-end coding, A/B testing, code review, and performance evaluation of various model versions, using metrics and user feedback to enhance model performance. Documented processes, scrum methodologies, Automation, and bestpractices to facilitate knowledge sharing and promote efficient collaboration within the team.• Developed a self-service, low code/no code platform following Agile principles, enabling data scientists to deploy data and ML models as APIs, including an advanced recommendation engine for enhanced user experiences and personalization.• Implemented Microservices architecture using Flask and FastAPI, integrating RESTful APIs and following an event-driven approach.• Designed and implemented a DevSecOps platform for data scientists, allowing them to leverage data engineering and batch processing capabilities with minimal manual intervention and experience in Preprod/Production Environment.• Leveraged various Azure & AWS integration tools, data factory & data lakes, SQL data warehouses, Azure Synapse analytics, load balancers, and version control tools like Git to achieve the desired product ionization functionality.• Integrated multiple databases, utilized Jenkins CI/CD data pipeline for ML model development, and deployed code and MLflow artifacts on Azure Kubernetes for container orchestration, automating testing and training processes.• Deployed a scalable system incorporating auto-scaling and CPU throttling techniques to manage data and JSON product recommendation models, yielding a substantial 75% reduction in costs while optimizing resource utilization.• Created interactive performance analysis dashboards using Tableau, New Relic, and Data Dog software, providing stakeholders with real-time monitoring capabilities for live applications and business KPIs

• Utilized Python and SQL to analyze extensive IT service management datasets, processing over 100,000 data points to extract valuable insights and contribute to the development of actionable recommendations..• Contributed to process reengineering initiatives, identifying, and implementing improvements that resulted in a 15% increase in IT service delivery efficiency.• Employed tools such as Tableau, along with MS Office and Qlik Sense, to create compelling visualizations that enhanced data understanding and decision-making.• Conducted trend analysis and forecasting on matrices of IT service management data, enabling the team to proactively address service needs. This resulted in a 10% reduction in IT service incidents.

Hyderabad, Telangana, India

• Performed process risk analysis study for hydraulic couplers through PFMEA to ensure risk-free production line processes.• Reduced defective parts in the production line to less than 5% by developing statistical process control analysis on an automobile prototype production project.• Collaborated with relational databases such as Oracle, SQL Server, MySQL, as well as NoSQL databases like MongoDB, to ensure optimal data storage and retrieval efficiency.• Reviewed and optimized inventory management flow within the organization, reducing processing time by 15%

Visakhapatnam, Andhra Pradesh, India

Undergone training in different departments of shipbuilding i.e HULL SHOP, PRE-FABRICATION, EKM & DESIGN DEPARTMENT

Master'S Degree, Business Analytics, 3.86

UB MSBA curriculum emphasized the development of analytical skills, advanced statistical techniques, and the use of technology to solve.

Bachelor Of Technology - Btech, Mechanical Engineering

Activities and Societies: SAE club, University Automobile Club, Team Vanquishers