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Software developer in pursuit of becoming Software Engineer Passionate about JS, Python - Machine Learning and AI
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
LiveLike
AI and Machine Learning Engineering
June 14, 2026 – Present
Mental-Wellness-Tracker
June 13, 2026 – Present
This is PromptWars Mumbai Challenge to build Mental Welness Tracker for applicants/students
View Projectlivelike-docs
September 8, 2025 – Present
LiveLike documents repository that contains CMS and platform guides, REST API references including Web, IOS, Android and React Native SDK
View Projectvocaber
May 27, 2025 – May 27, 2025
A Gamified Vocabulary enhancement application where user could create and join competitions and penalise one and another for any vocabulary improvements
View Projectadvent-of-code-2022
December 4, 2022 – December 4, 2022
This Repo solves Advent of Code 2022 puzzles in Javascript
View ProjectrsyncBackup
December 29, 2018 – December 30, 2018
Multiplatform GUI for rsync Backup using electron.js and react
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards personal projects, many of which involve web development and some problem-solving challenges. The target role is 'AI and Machine Learning Engineering', but the projects primarily showcase front-end and general programming skills (JavaScript, TypeScript, HTML, CSS). There is a significant gap between the demonstrated project skills and the target AI/ML role, which suggests a potential mismatch in current technical alignment, though it could indicate a desire to transition. The single listed work experience is current and also in 'AI and Machine Learning Engineering', but without details on responsibilities or achievements, it's hard to assess its depth or relevance.
Soft Skills & Operational Fit
The provided data does not contain sufficient information to assess soft skills or operational fit. Project descriptions are brief, and there are no interview notes or peer feedback.