I am the Lead DevOps Engineer at UBC Agrobot, a design team focused on designing autonomous agriculture robots and their support systems. The team repositories can be seen here. Some of my notable contributions as sub-team lead can be seen below.

• Designed and implemented CI/CD pipelines using GitHub Actions to eliminate manual build and deployment operations, streamlining release cycles by 65%.
• Reduced system setup times by 30% using custom multi-platform Docker containers to automate local and staging environment setup and eliminate dependency issues for over 20 developers.
• Configured dynamic Grafana dashboards with Prometheus metrics to visualize data streams from multiple internal tools, improving the visibility of key system statistics.

As a Software Engineer working in undergraduate research, I worked to define and implement data storage systems and perform data analysis. Although none of the code or systems I have developed are public, here is a summary of my biggest accomplishments:

• Architected a PostgreSQL database schema supporting 10+ tables and indexes, improving data retrieval times by 62% through the integration of Redis in-memory caching.
• Implemented a backend API layer in Python using Flask-RESTful, yielding monthly savings of 112 person-hours by abstracting database queries.
• Performed exploratory data analysis using NumPy and Pandas, identifying key data trends and patterns, which were visualized with Seaborn and Matplotlib.
• Cleaned and transformed datasets using Excel, then built PowerBI dashboards that communicated insights to internal teams, improving decision-making efficiency.

I formerly worked on the embedded systems subteam for UBC Agrobot, focusing on developing real-time software applications applications and optimizing ML image processing using computer vision and GPU optimization techniques, my primary achievements include:

• Led a team of 8 engineers and engaged in system architecture reviews, revamping inter-process communication using C++, Python and ROS2, reducing system-wide latency by over 90%.
• Optimized image streaming inference using multi-threading and GPU optimization libraries in an Nvidia Jetson Linux development environment, increasing system throughput by 5x.
• Spearheaded the development of automated unit, integration and performance testing infrastructure with PyTest and Bash, accelerating sprint delivery by 35%.
• Identified and resolved 7+ system bottlenecks using profiling and function trace reports from Py-Spy, perf and Nsight Systems, ensuring robust code functionality.

• Constructed GoLang application to query REST/GraphQL APIs upon receiving webhook payloads and send notifications to users on alternative platforms, increasing response times by 20%.

• Developed infrastructure-as-code templates on AWS using Terraform, and automated container deployments using Kubernetes/Helm, powering a cloud-hosted movie recommendation website.

• Created a collection of Python scripts for automating common tasks, including web scraping, data analysis, and file manipulation, saving 10 hours of manual work per week.