Mohit Kumar Email & Phone Number

Nurpur, HP, IN

Bengaluru, Karnataka, India

• Designed and engineered responsive user interfaces, driving the development and maintenance of 12+ Agile projects with a focus on performance and scalability.
• Led the SDUI initiative, implementing advanced architectures like module federation and micro frontends with Next.js, optimizing modularity and deployment flexibility across applications.
• Optimized application performance, reducing page load times by 12%, directly enhancing user experience and overall system responsiveness.
• Improved project efficiency by 37% through full-stack development expertise, delivering high-quality software solutions and contributing to streamlined project execution.
• Collaborated with cross-functional teams—developers, business analysts, and architects—to develop and maintain 12+ web-based enterprise applications, leveraging React, JavaScript, and Java technologies.
• Achieved a 23% reduction in software issues, actively contributing to the entire SDLC through design, development, rigorous testing, and systematic bug resolution.

Remote

• Worked with Google Summer of Docs technical writers to develop a complete module development documentation using FLINT at moja global.
• Collaborated with the Technical Steering Committee to spearhead a Documentation working group of 140+ volunteers to contribute to moja global's open-sourced documentation.
• Mentoring, assisting, and guiding fellow contributors under the moja global umbrella; Led a 400+% growth in the community size over six months.
• Tech Stack: Markdown, C++, Git, Sphinx, Markdown, GitHub Actions, JavaScript

Hamirpur, Himachal Pradesh, India

• Worked as a problem setter for our Institute’s monthly contest series, Heuristics, made around 90+ coding problems and hosted 7 heuristics rounds on the codeforces and codechef.
• Contests were built using Codeforces Polygon Platform, promoting the growth rate of participants in the contest to around 200%.
• Managed 15+ events and workshops of the departmental Computer Science team at NITH with around 300+ participants.

India

• Implemented a Long short-term memory (LSTM) recurrent neural network(RNN) for Web traffic time series forecasting.
• Published blogs on various Machine Learning Algorithms.
• Performed Data preprocessing and optimized the performance of the LSTM-RNN from 78% to 84% accuracy rate.
• Tech Stack: Python, Keras, Tensorflow, Scikit-learn, Numpy, Javascript.