Email: [email protected] | Phone: 778-222-1023 | GitHub: github.com/kemkemG0 | LinkedIn: linkedin.com/in/kemkemg0

University of British Columbia - BSc in Computer Science, 4th year | Vancouver, BC, (Apr 2025 Grad)

• Engineered a natural language search engine leveraging Qdrant on AWS EKS, enhancing query accuracy with RAG implementation for advanced processing.
• Pioneered the development of a conversion pipeline to transform natural language queries into vector embeddings, significantly improving search functionality.
• Constructed a high-performance REST API server using Go, designed to interface seamlessly with a machine learning server, facilitating efficient data processing and retrieval.
• Orchestrated the deployment of multiple microservices using AWS ECS, ensuring their optimal cooperation and functionality within the search engine ecosystem. Fostered a culture of innovation and team collaboration.

• Spearheaded the full-scratch development and architectural design of a complex system that bridges user-initiated events with a dedicated microservice for comprehensive data analysis.
• Developed and deployed a Go-based Dataflow job, optimizing the processing pipeline for event ingestion from Cloud Pubsub, enhancing throughput and data flow within GCP's ecosystem.
• Executed the integration of advanced real-time monitoring tools, including Sentry and Datadog, to uphold system reliability and stability, achieving exceptional system uptime.
• Amplified the robustness of End-to-End (E2E) testing frameworks to support multiple communication channels, automating test processes and database deployment using Cloud Spanner and BigQuery, which resulted in a 50% reduction in E2E test execution times.

• Directing the development of a state-of-the-art Know Your Client (KYC) web application tailored for the legal sector, encompassing comprehensive phases from conceptualization to deployment.
• Implementing the front-end with Nuxt.js and architecting a Typescript-powered Express back-end, all within a Docker compose orchestrated environment for enhanced scalability and maintainability.
• Strategically deploying the back-end on AWS ECS and the front-end on AWS Amplify, employing Terraform for infrastructure management, which enables swift transitions and rollbacks between staging and production environments.

• Collaborated on a team to develop a sophisticated abnormality detection program, using Python and machine learning algorithms, which substantially increased the precision of defect identification in manufacturing.
• Implemented an OCR tool for financial document analysis, converting PDFs and images to actionable data formats, thereby streamlining data extraction processes.
• Contributed to the enhancement of large-scale web applications, addressing feature additions and bug resolutions, and employing a diverse stack that includes React with Typescript, Express, Django, and Laravel for full-stack development capabilities.

• Contributed to Qdrant, a Rust-based high-performance distributed vector database:
  • Abstracted snapshot functionality to support various cloud storage solutions, not just local storage.
    • Link to the PR: qdrant/qdrant#4150
  • Resolved an issue where data insertion would crash due to insufficient storage, proposing and implementing DiskMonitoringManager for heuristic capacity monitoring.
    • Link to the PR: qdrant/qdrant#4165
  • Earned approximately $700 USD in bounties for these contributions.

• Achieved a top 15% ranking in competitive programming, demonstrating strong problem-solving abilities and proficiency in algorithms.