ARYAN
SHARMA
Creative Developer building high-performance systems.
EXPERIENCE/
ACM Student Chapter, MUJ
Jaipur, India
Technical Head
April 2026 – Present
Leading technical direction for chapter projects, ensuring structured development practices and scalable system design.
Collaborating with cross-functional teams to design and implement scalable solutions for chapter-wide use.
Promoting a project-driven learning approach, enabling members to gain end-to-end development exposure.
Web Development Junior Committee
November 2025 – April 2026
Spearheaded the development of 3+ responsive event websites, optimizing for heavy traffic.
Contributed to the development of a Certificate distribution platform, enabling automated generation and delivery of certificates for large scale ACM events.
Collaborated with team to ensure smooth deployment and reliability during live events.
Freelance
Remote
Freelance Full-Stack Developer
January 2026 – Present
Engineered a sales distribution platform for client, integrating order management and live salesman tracking that reduced administrative overhead by 40%.
Architected responsive admin dashboards using React and JavaScript to manage complex partner access controls.
(01) The Ethos
Full-stackdeveloperfocusedonhigh-concurrencybackendsystemsandAI-drivenarchitecture.Ibridgethegapbetweencomplexsystemdesignandintuitive,production-readyinterfaces.
(02) Selected Works
Blytz
The high-speed README architect.A high-speed CLI Tool using Node.js to automate the generation and maintenance of professional project READMEs. Auto-scans, auto-weaves, and auto-maintains professional project docs. Achieved 1000+ downloads in the first week of release. Zero-config CLI + GitHub App.
VoteAway
Real-time voting at scale.A real-time voting and leaderboard system for 1,500+ users. High concurrency platform with sub-100ms latency, atomic Redis vote locking, smart polling via SWR, Google OAuth2, and an admin control panel for secure, scalable voting.
Creator Trust
AI-powered influencer authenticity.A full-stack platform to evaluate influencer authenticity and recommend fair pricing using behavioral signals. Built a Random Forest-based scoring system (R² ≈ 0.92, MAE < 3) with feature engineering on engagement rate, comment uniqueness, and growth volatility.
SWAN
AI reviewer extension for Amazon.A Chrome Extension using Google Gemini API to generate concise sentiment summaries from hundreds of Amazon reviews. Features a DOM-based scraping engine to extract product data directly into a browser side panel. Reduced average product research time by an estimated 70% through automated summarization.