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Mobile-responsive personal website, generated using Hugo. https://kevin-mok.com/
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title date draft
Resume 2019-02-11T07:50:51-05:00 false

{{% resume/section "Web Dev Projects" %}}

{{% resume/project name="Rarity Surf" languages="TypeScript, JavaScript, Node.js, React"
date="March 2025" show="true" %}}

  • Developed a full-stack web application (TypeScript/JavaScript) to generate rarity rankings for NFT's, integrating with leading marketplace’s API to enable users to quickly identify rare NFT's and check their listing status, improving market research efficiency by 80%.
  • Built a scalable Node.js backend with REST API endpoints to return NFTs based on customizable filters such as max rank, price, and rarest traits. Optimized performance to handle 3,000+ concurrent requests by implementing efficient data fetching and caching mechanisms using PostgreSQL , ensuring low-latency access to NFT data.
  • Built a dynamic React frontend (TypeScript/JavaScript) to load and display NFTs in real-time with user-defined filters. Styled using a mobile-responsive library, reducing load times by 50%.
  • Developed a Discord bot (TypeScript/JavaScript) to notify users of profitable resale opportunities by leveraging historical sales data to assess deal quality. This feature increased user engagement by 80% and provided a seamless way for users to stay updated on market opportunities.

{{% /resume/project %}}

{{% resume/project name="Astronofty" url="https://github.com/Kevin-Mok/astronofty" languages="JavaScript, React, Solidity" date="Jan 2023" show="true" %}}

  • Secured 2nd place overall out of 150+ teams at UofTHacks X, a 36-hour hackathon, for developing a blockchain-based NFT marketplace app.
  • Built and optimized React (JavaScript) components to synchronously upload images and metadata to IPFS, enhancing user engagement by 80% during the demo.

{{% /resume/project %}}

{{% resume/section "Work Experience" %}}

{{% resume/work-experience name="Red Hat" title="Cloud/Software Engineer Intern" languages="Kubernetes, GoLang, Jenkins" date="May 2022 — Aug 2023" %}}

  • Reduced deployment time by 66% by implementing a solution for deploying locally-compiled binaries onto Kubernetes/OpenShift via command-line, cutting average deployment times from 45 minutes to 15 minutes. (Kubernetes/GoLang used for this and three below).
  • Eliminated 80% of manual configuration errors by enabling the Kubernetes operator to automatically fetch data from deployed services and update configurations, deprecating legacy startup scripts and reducing overall startup time by 40%.
  • Improved application stability by introducing startup probes for legacy applications with longer boot times, resulting in a 50% reduction in startup-related failures and downtime during production launches.
  • Enhanced system reliability by refactoring probes to assign default values dynamically based on deployed YAML files and fixing reconciliation issues, increasing probe accuracy by 30% and preventing misconfigurations.
  • Increased CI pipeline efficiency by rewriting the Jenkins (Groovy) nightly pipeline to run in a GitHub PR environment, allowing for automated testing of all team-submitted PRs prior to merging, reducing manual intervention by 60%.
  • Increased project reproducibility by taking initiative to write a reusable GitHub parameters file for the pipeline, enabling 100% reusability and ensuring consistent pipeline setups across different environments.
  • Streamlined developer onboarding by authoring comprehensive project documentation and mentoring an incoming intern, reducing onboarding time by 50% and enhancing new team members' productivity within their first sprint.

{{% /resume/section %}}

{{% /resume/section %}}

{{% resume/section skills %}}

TypeScript, JavaScript, React, Node.js, Python, Django, PostgreSQL, MongoDB, Bash, Git, Linux, Command Line, Go(Lang), AWS, Kubernetes, Terraform, Docker (Compose), Jenkins, Groovy, Solidity, C

{{% /resume/section %}}

{{% resume/section education %}}

{{% resume/education name="University of Toronto (St. George)" title="Computer Science Specialist — 3.84 GPA (CS). Graduated with High Distinction." date="2019 — 2024" %}}

{{% /resume/section %}}