Open to AI Engineering Internships & Entry-Level Opportunities

Building Intelligent Software.
Engineering with Purpose.

I’m a Computer Science student and aspiring AI Engineer with 3+ years of accumulated programming knowledge, building practical software and AI-powered tools. I value security, continuous learning, and engineering solutions that solve real problems.

Focus
AI Engineering / CS Student
Experience
3+ yrs programming knowledge
Approach
Secure · Local-first · Practical
Portrait of Hanz Joseph Canda
Hanz Joseph Canda CS Student · Aspiring AI Engineer

About Me

A student engineer learning by building real things.

I’m studying for a Bachelor of Science in Computer Science and have accumulated more than three years of programming knowledge — learning, experimenting, and building software project after project.

I enjoy building practical applications and exploring AI engineering: developing, integrating, evaluating, and improving AI-powered software. My projects are local-first machine-learning tools — regression, classification, retrieval, summarization, and anomaly detection — built with Python, scikit-learn, FastAPI, TypeScript, and React.

I prioritize security, reliability, maintainability, and responsible handling of data in everything I build. I adapt to new tools, languages, frameworks, and workflows, and I approach challenging problems as opportunities to improve.

Right now I want to gain practical industry experience while continuing my education — contributing to meaningful work, learning from experienced engineers, and growing into a professional AI Engineer. I welcome mentorship, constructive feedback, and opportunities to collaborate.

  • 7ML projects shipped to GitHub
  • 3+years of programming knowledge
  • 100%local-first, privacy-conscious builds

Technical Skills

What I work with.

Skills below marked Hands-on are verified in my shipped repositories. Those marked Learning are technologies I’m actively studying next — no inflated claims, no invented percentages.

Programming & Software Development

  • Hands-onPython
  • Hands-onTypeScript
  • Hands-onJavaScript
  • Hands-onSQL (SQLite)
  • Hands-onOOP
  • Hands-onData structures & algorithms
  • Hands-onGit & GitHub

AI & Machine Learning

  • Hands-onML fundamentals
  • Hands-onData preprocessing & analysis
  • Hands-onModel evaluation
  • Hands-onAI app development
  • Hands-onNLP basics (TF-IDF)
  • Hands-onExperimentation & benchmarking
  • Hands-onModel inference fundamentals

AI Engineering Ecosystem

  • Hands-onNumPy
  • Hands-onpandas
  • Hands-onscikit-learn
  • Hands-onFastAPI
  • Hands-onJupyter
  • LearningPyTorch
  • LearningTensorFlow
  • LearningHugging Face Transformers

Web & Application Development

  • Hands-onREST APIs
  • Hands-onReact
  • Hands-onVite
  • Hands-onResponsive UI design
  • Hands-onDatabase integration
  • Hands-onJSON & data processing
  • Hands-onStreamlit

Security & Reliable Engineering

  • Hands-onSecure coding practices
  • Hands-onInput validation
  • Hands-onAuth fundamentals
  • Hands-onSecrets management
  • Hands-onData privacy
  • Hands-onLogging & error handling
  • Hands-onTesting (pytest · Vitest)

Tools & Infrastructure

  • Hands-onLinux & CLI tools
  • Hands-onVirtual environments
  • Hands-onEnvironment configuration
  • LearningDocker
  • LearningCI/CD fundamentals

Featured Work

Seven projects. One engineering philosophy.

Every project below is a real repository on my GitHub — local-first, CPU-only, and documented with honest limitations. Descriptions reflect the actual code, not the names.

Engineering Principles

How I approach building software.

These are principles I value and work toward — aspirations that guide my builds, not claims that every project already satisfies each one perfectly.

Security by Design

Consider security throughout development — input validation, safe configuration, dependency hygiene, data protection, and appropriate access controls.

Responsible AI

Value transparent limitations, meaningful evaluation, privacy-conscious data handling, and careful interpretation of model outputs.

Practical Problem Solving

Build tools that address concrete problems rather than adding AI merely for appearance.

Maintainable Architecture

Prefer understandable code, modular design, appropriate abstractions, useful documentation, and consistent conventions.

Continuous Learning

Learn new technologies through experimentation, documentation, implementation, and feedback.

Performance & Accessibility

Consider resource constraints, efficient execution, usability, and accessibility — software should work for everyone, on modest hardware.

Learning & Growth

Growing Through Real Engineering Work

I’m looking for opportunities where I can contribute to meaningful projects, learn from experienced engineers, and strengthen my AI engineering skills through real-world work. I adapt to unfamiliar tools, welcome feedback, and approach challenging problems as opportunities to improve. I want to build reliable, secure, and useful AI-powered systems while continuing my Computer Science education.

  • AI Engineering internships
  • Junior AI / ML engineering opportunities
  • Entry-level software roles involving AI
  • Collaborative research & development
  • Open-source contributions
  • Mentorship & technical collaboration

I understand AI engineering is also software engineering — data pipelines, testing, deployment, and system reliability — and I’m ready to do that work, not just train models.

Contact

Let’s Build Something Intelligent.

I’m interested in opportunities where I can contribute, learn, and grow as an engineer. If you’re looking for a motivated Computer Science student interested in AI, software development, and secure engineering, I’d be glad to connect.

Send Me an Email