I am a passionate Software Engineer with a strong focus on building scalable, high-performance systems. My expertise spans across AI/ML engineering, full-stack development, and product engineering — with a mindset centered on delivering production-grade solutions that solve real-world problems.
I thrive in environments that demand clean architecture, algorithmic rigor, and the ability to ship products from concept to deployment. Whether it's designing distributed backends, crafting intuitive frontends, or training ML models — I approach every problem with engineering discipline and a growth mindset.
- Roles: Software Engineering, AI/ML Engineering, Full Stack Development
- Industries: Tech, Fintech, AI/ML, SaaS, Product Companies
- Work Types: Full-time | Remote | Freelance Projects
| Category | Skills | Level |
|---|---|---|
| Languages | Python · JavaScript · TypeScript · Go | 🟣🟣🟣🟣🟣 |
| Backend | FastAPI · Django · Node.js · Express | 🟣🟣🟣🟣🟠 |
| Frontend | React · Next.js · Tailwind CSS | 🟣🟣🟣🟣🟠 |
| AI / ML | PyTorch · TensorFlow · Hugging Face | 🟣🟣🟣🟠🟠 |
| Databases | PostgreSQL · MongoDB · Redis | 🟣🟣🟣🟣🟠 |
| DevOps | Docker · Kubernetes · AWS · GCP | 🟣🟣🟣🟠🟠 |
| System Design | Microservices · API Design · Caching | 🟣🟣🟣🟣🟠 |
| Problem Solving | Algorithms · Data Structures · DSA | 🟣🟣🟣🟣🟣 |
| Domain | Level | Details |
|---|---|---|
| Machine Learning | Advanced | Scikit-learn, XGBoost, LightGBM, model training & evaluation |
| Deep Learning | Intermediate | TensorFlow, PyTorch, neural network design & training |
| NLP / LLMs | Intermediate | Hugging Face, RAG systems, prompt engineering, fine-tuning |
| Computer Vision | Intermediate | OpenCV, image classification, object detection pipelines |
| MLOps | Intermediate | MLflow, model versioning, deployment pipelines, monitoring |
| AI Productization | Advanced | End-to-end AI system design: data → training → inference → scale |
🔷 Project Name — One-Line Description
Project description: A brief, impactful description of what this project does and the problem it solves.
| Attribute | Detail |
|---|---|
| Stack | React, Node.js, PostgreSQL, AWS |
| Scale | 10K+ users, 1M+ API requests/month |
| Performance | 99.9% uptime, <100ms p95 latency |
| Security | OAuth 2.0, JWT, encrypted data at rest |
| Impact | Reduced operational costs by 40% |
| Repository | 🔒 Private / Coming Soon |
Add a brief professional explanation of your role, the technical challenges you solved, and the outcome.
🔷 Project Name — One-Line Description
Project description: A brief, impactful description of what this project does and the problem it solves.
| Attribute | Detail |
|---|---|
| Stack | Python, FastAPI, Redis, Docker, GCP |
| Scale | 50K+ inferences/day |
| Performance | <50ms avg inference time |
| Security | Role-based access, audit logging |
| Impact | Enabled real-time decision-making for 200+ users |
| Repository | 🔒 Private / Coming Soon |
Add a brief professional explanation of your role, the technical challenges you solved, and the outcome.
Company Name · Location
MMM YYYY – Present
- Designed and built scalable microservices handling 1M+ daily requests with 99.9% uptime
- Led migration of monolithic architecture to event-driven microservices using Kafka and Docker
- Implemented CI/CD pipelines with GitHub Actions, reducing deployment time by 70%
- Collaborated cross-functionally with product, design, and data science teams
Skills: Python · Django · FastAPI · PostgreSQL · Redis · Docker · Kubernetes · AWS
| Recognition | Details |
|---|---|
| Top Performer | Recognized for shipping a critical feature 2 weeks ahead of schedule |
| Open Source Contribution | Active contributor to Python and JavaScript open-source projects |
| Code Quality | Maintained 95%+ test coverage across all maintained repositories |
| System Reliability | Built systems with zero critical incidents in production for 12+ months |
⚡ Run manually: Actions tab → Generate Contribution Snake → Run workflow
Connect Spotify via https://github.com/zuhair321 (Spotify section coming soon — working on it!)
Learning:
- Advanced system design & distributed systems
- Large language models & AI agent architectures
- Cloud-native security patterns
Building:
- Scalable backend microservices
- AI-powered applications
- Open-source tools & libraries
Exploring:
- MLOps & model deployment at scale
- Real-time data pipelines
- Product-led growth strategies
Open To:
- Software engineering opportunities
- AI/ML engineering roles
- Collaboration on interesting projects"Code is not just logic — it's craft, discipline, and the relentless pursuit of elegance."