th1nhng0

Location: Ho Chi Minh City, Vietnam / GMT+7

Remote: Yes

Willing to relocate: No, remote preferred

Technologies: Python, TypeScript, JavaScript, React, Next.js, React Native, Astro, Node.js, Bun, Docker, Linux, Coolify, React Query, Zustand, shadcn/ui, C++, Generative AI, prompt engineering, AI integration, model fine-tuning, ComfyUI / Stable Diffusion

Résumé/CV: https://thinhcorner.com/ | GitHub: https://github.com/Th1nhNg0 | LinkedIn: https://www.linkedin.com/in/th1nhng0/

Email: thinhngow@gmail.com

I’m Ngô Phú Thịnh, a software engineer based in Ho Chi Minh City, Vietnam, looking for remote roles in AI, automation, web development, or product engineering.

I’m especially interested in building practical AI-powered tools, automation systems, internal tools, data workflows, web apps, and products that combine software engineering with applied AI. I have experience developing web and mobile applications, designing system architectures, maintaining data pipelines, and building e-commerce platforms, landing pages, and data-analysis algorithms for startups.

My background is a mix of software engineering, data science, and research. I graduated from the University of Science, VNU-HCM with a Bachelor’s in Mathematics and Computer Science, specializing in Data Science, and I’m currently pursuing an MBA at UEH. I’ve also published research on legal information retrieval, AI for Vietnamese labor law, and human-in-the-loop annotation.

Some areas I’d be excited to work on: - AI automation / workflow automation - AI agents, LLM integrations, RAG, search, and retrieval systems - Web apps, dashboards, internal tools, and SaaS products - Data pipelines, scraping, analysis, and automation - Legal-tech, edtech, productivity tools, or developer tools - Frontend, full-stack, or product-focused engineering

I’m adaptable, curious, comfortable learning quickly, and happy to work across the stack from research/prototyping to production implementation.

cool project

Thanks, these are all excellent suggestions.

The "distance to goal" constraint is a clever idea, though it's tricky to implement because the tunnels act as teleporters, so a simple distance metric doesn't apply. I'd likely need to pre-calculate a shortest-path graph first.

I'm benchmarking Huub and Pumpkin now. My main goal is raw performance, as a friend's imperative brute-force solver (https://github.com/FoxtrotOnce/RailboundSolver) solves most levels in under 2 seconds. It's a high bar to meet with a declarative model, but I'm keen to see how close I can get with these optimizations.

I've also just pushed some initial benchmarks for Chuffed vs. OR-Tools to the repo if you're interested (https://github.com/Th1nhNg0/railbound_cp/tree/master/docs/be...). Thanks again for the great feedback!

Thanks for the great feedback! I didn't know OR-Tools CP-SAT worked best with at least 8 threads; I'll definitely try that out.

In my local tests, Chuffed is often faster on the simpler instances. However, I've noticed on the harder puzzles, Chuffed can take over 10 minutes, while OR-Tools (with just 4 threads) solves them in about 5.

You're also right about the records. I started with tuples for simplicity, but as the model grew more complex, it's clear that records would be a much better approach for readability.

I have read that article too and very interest in the solver

We are on the same boat

wow, I never expect that xD thanks for let me know

Can I ask how you draw the chart in the post?

no :D

Oh thanks

Really cool project