Sai Medhini Reddy Maryada

- Led development and maintenance of multiple OpenSearch client libraries—opensearch-py, opensearch-php, and opensearch-api-specification—delivering new features, resolving security vulnerabilities, and fostering community adoption. Reviewed 100+ PRs, mentored junior engineers, and created a contributor tutorial video with 2K+ views. - Automated API generation pipelines for Python and PHP clients using OpenSearch API specifications, doubling API surface area and test coverage. Built robust CI/CD pipelines via GitHub Actions, ensuring support for 450+ customer-facing APIs with strong backward compatibility guarantees. Introduced YAML-based test runners in opensearch-py to streamline regression testing. - Consolidated the Python client stack by merging opensearch-dsl-py into opensearch-py, significantly reducing maintenance overhead. Led the entire migration effort, including porting tests, updating documentation, and planning a seamless developer transition. - Delivered full-stack features for the Dashboards Flow Framework using React.js, TypeScript, Redux, and Jest/Cypress. Authored ~90% of test coverage, added key UI components, and fixed critical bugs for a stable and scalable frontend experience. - Integrated next-gen OpenSearch UI and implemented support for Amazon OpenSearch Serverless (AOSS) datasources and Neural Sparse Search presets. Led end-to-end delivery, resolved complex versioning challenges, and enabled seamless onboarding for embedding models and LLM workflows. - Drove release engineering efforts across open-source, managed service, and private beta releases. Managed pipelines, handled infra setup, and worked directly with beta customers to support ML integration and private infrastructure readiness. - Enhanced the OpenSearch Benchmarking Framework by implementing a Client Processing Time metric to isolate client-side latency from total request time, helping diagnose performance bottlenecks in API interactions.

● Pioneered an Android based application for internal use of “Mars” company. ● Played a key role in every step of Development and Automation of Employee Satisfaction Assessment App. ● This application is tested in one of the Mars offices and observed a reduced attrition rate of 32%. ● Tools used: Microsoft Power Apps, Microsoft Power Automate, HTML, CSS and Microsoft Dataverse. ● Attended a variety of training sessions including Python, R and SQL . ● Acquired good technical and problem solving knowledge by doing Data Science courses namely- Introduction to Data Analytics for Business, Databases and SQL for Data Science, Data Science with Python.

● Helped the FMCG vertical by comparing the revenue generated by each client for Quantium against their market sales to prioritize business development opportunities. ● Worked for Sanofi, a global biopharmaceutical company, on projects including product pricing, promotional effectiveness calculation, segment-wise sales analysis and delivered dashboards. ● Migrated multiple critical workpieces from Teradata to Snowflake and also from Scala to Pyspark. ● Provided insights on customer purchase patterns during COVID for FMCGs by analyzing the customer data of Woolworths, an Australian retail company.

Performed a Study on Machining equipment and made a report on their performance.

Developed clamping jaws for machining Aakash missile component front-end utilizing Catia for design, Ansys for analysis and CNC machines for manufacturing.