Nachiket Kolte

Detail-oriented software developer with a focus on delivering robust, high-quality solutions. I take the time to fully understand project requirements before implementation, ensuring consistent and reliable outcomes. Committed to following best practices and industry standards, I'm always ready to work hard and adapt to achieve the desired results. A strong advocate for clean code, I strive for continuous improvement in every project.

• End of Line Software Developement: Developed a comprehensive application for automating device validation in multiple international manufacturing plants using Python, FastAPI, and Websockets. Increased testing throughput by 30% and improved test accuracy across multiple global locations.
• Device Communication Tool: Designed a web-based interface for real-time communication with factory devices (controllers, inverters). Enabled parameter read/write, firmware updates, and project downloads over Ethernet and CAN interfaces. Increased operational efficiency and reduced manual intervention during firmware updates.
• Automation Test Runner Tool: Built a single-stop web UI to automate complex test configurations and execution. Allowed users to configure test parameters, select test cases, and execute them with real-time logging and result display. Replaced manual config file handling with a dynamic UI. Reduced test setup time by 95% and improved logging accuracy.
• Automation of Cybersecurity Compliance Verification: Developed a solution to assess cybersecurity aspects of controllers and devices, ensuring compliance with the latest European Union regulations.
• Timesheet Updater: Developed a timesheet automation tool that allows users to select assigned tasks from a dynamic UI, enter working hours, and auto-populate the timesheet. Pulled task data from MPP and automated the submission process, minimizing human error. Cut down timesheet filling time by 70% and reduced task selection errors.
• Timesheet Validator: Enhanced team productivity by automating the validation of timesheets against MPP task data. The tool provides a dashboard displaying errors, coding time, analysis time, and leave records, improving data accuracy and reducing manual effort. Reduced errors in timesheets by over 90%, improved reporting efficiency and teams credibility.
• Handwritten Devanagari Character Recognition: Built a deep learning model using ResNet to accurately recognize handwritten Devanagari characters, optimizing for high accuracy.