John Doe

Professional ATS-optimized resume template for Frontend Developer In Ai positions

John Doe

Frontend Developer | AI & Machine Learning Enthusiast

Email: john.doe@email.com | Phone: (123) 456-7890 | LinkedIn: linkedin.com/in/johndoe | GitHub: github.com/johndoe

PROFESSIONAL SUMMARY

Innovative Frontend Developer specializing in AI-driven web applications with over 5 years of experience delivering dynamic, user-centric interfaces. Adept at translating complex AI models into intuitive visualizations and engaging user experiences. Skilled in leveraging the latest frontend frameworks, integrating machine learning APIs, and optimizing performance for high-volume platforms. Passionate about pushing the boundaries of AI-powered frontends to enhance user engagement, accessibility, and real-time interactivity.

SKILLS

Hard Skills

- React.js, Vue.js, Angular

- TypeScript, JavaScript (ES2025)

- WebGL & Three.js for 3D AI visualizations

- REST & GraphQL API integration

- TensorFlow.js, ONNX.js for client-side ML

- WebAssembly for high-performance AI tasks

- CSS3, SASS, TailwindCSS

- Version Control: Git, GitHub, GitLab

- Build Tools: Webpack, Vite, Babel

- Continuous Integration/Deployment (CI/CD)

Soft Skills

- Creative problem solving

- Cross-functional collaboration

- UX-focused development

- Agile methodologies

- Critical thinking and adaptability

- User accessibility awareness

EDUCATION

**Bachelor of Science in Computer Science**

University of Texas at Austin, TX

Graduated: 2018

CERTIFICATIONS

- Certified Front-End Developer — W3Schools (2021)

- TensorFlow Developer Certificate — Google (2022)

- Advanced JavaScript & TypeScript — Pluralsight (2023)

- AI and Machine Learning for Frontend Developers — Coursera (2024)

PROJECTS

AI-Powered Data Visualization Tool

- Developed an interactive web app using React and WebGL, visualizing complex datasets through AI-generated 3D models. Enabled users to manipulate data in real-time with machine learning insights.

Real-Time Emotion Detection Web App

- Built a browser-based application integrating TensorFlow.js models for facial emotion detection during live video streams. Enabled seamless user experiences with minimal latency.

Accessibility-Focused AI Dashboard

- Led the creation of an accessible dashboard for monitoring NLP model accuracy, following WCAG standards and ensuring compatibility with assistive technologies.

TOOLS & TECHNOLOGIES

- Frameworks: React.js, Vue.js, Angular

- Languages: JavaScript (ES2025), TypeScript, WebAssembly

- Libraries: TensorFlow.js, D3.js, Three.js, TailwindCSS

- Platforms: AWS Amplify, Netlify, Vercel

- DevOps: GitHub Actions, Docker, Vite

LANGUAGES

- English (Native)

- Spanish (Professional Proficiency)

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