Vinay Malankad
UI Engineer at www.rowsncolumns.app
Singapore
Summary
🤩
Rockstar🎓
Top SchoolVinay Malankad is a senior UI engineer based in Singapore with 15 years of experience building high-performance JavaScript applications for both startups and major financial institutions. He combines deep expertise in React, functional programming and design systems with a proven track record of shipping low-latency trading UIs at Citadel Securities and Risk/PnL platforms at Bank of America. As a founder he launched and quickly sold a spreadsheet-style grid product that hit Hacker News, and he’s led teams to high test coverage and strong engineering practices. Vinay mentors and hires engineers, authors reusable component libraries and drives end-to-end delivery including CI/CD and performance tuning. He also has hands-on ML/NLU experience from earlier product work and has contributed parsing logic to an open-source chatbot project. That blend of product-led engineering, performance-first front-end craft, and occasional backend/ML contributions makes him a pragmatic technical leader who ships polished, scalable UIs.
15 years of coding experience
9 years of employment as a software developer
Bachelors, Electrical and Electronics Engineering (Major in Infocomm), Bachelors, Electrical and Electronics Engineering (Major in Infocomm) at Nanyang Technological UniversityDiploma, Mechatronics, Diploma, Mechatronics at Singapore Polytechnic
English, Spanish, Hindi, Malayalam, Tamil
Github Skills (11)
regular-expression10
nlp10
python10
natural-language-processing10
lang8
machine-learning6
googlebot5
chatbot5
conversations5
conversation5
bots5
Programming languages (10)
Github contributions (5)
gunthercox/ChatterBot
Oct 2016 - Nov 2016
ChatterBot is a machine learning, conversational dialog engine for creating chat bots
Role in this project:
Back-end Developer
Back-end DeveloperContributions:19 commits, 4 PRs, 1 push in 1 month
Contributions summary:Vinay primarily contributed to the development of a date parsing module for the chatbot. The commits demonstrate the creation and enhancement of regular expressions to extract temporal expressions from text. The code changes involve defining functions and classes to convert natural language date and time references into usable datetime objects using the Python datetime and calendar libraries, and implementing unit tests.
nlppythondialogconversationalbot
rmdort/react-flexi-textarea
Nov 2015 - Oct 2017
Contributions:30 commits, 19 pushes, 6 branches in 2 years
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