• Overview: Built a project-based code challenge platform, ONE INTERVIEW, for employers to evaluate their candidates. Candidates’ qualification and level are rated automatically and properly by the machine-learning model we built.
• Code Evaluation Service
• Built tools that can integrate different open source libraries with our code challenge platform and extract signals from the code in different languages (Python, Ruby, Java, JavaScript, C++, swift, etc.) to generate coverage report, linter report, etc.
• Provided standardized data (ex. coverage percentages, errors, warnings, etc.) among different languages to the machine-learning model with 20% performance improvement.
• Integrated the evaluation service into the encapsulated Docker container, which is a lightweight virtual machine, to ensure isolation and performance.
• Web Development (Ruby on Rails, AWS)
• Built the whitelist to allow candidates to take multiple challenges upon requests from employers.
• Increased the website responsiveness by 70% using the combination of media queries and better assets compression to download suitable assets based on browsing devices.
• Code Challenge Performance Data visualization (c3.js & d3.js)
• Used d3.js and c3.js to build an interactive performance breakdown dashboard for employers to easily understand each candidate’s ability among different coding skills with multiple visualized charts.
• Expanding supportive language (Swift) and project-based code challenges
• Refactored the logic of supportive languages of our platform and configured the environment of the evaluation service (backend) to support swift, as well as the online editor (frontend).
• Expanded the pool of the code challenges with the corresponding solution, and ported it into different languages. (Python, Ruby, Java, JavaScript, C++, swift, etc.)
