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wasaydelivers

Abdul Wasay

@wasaydelivers

AI Engineer: Specialized in ML and MLOps

Pakistan
Engels, Urdu
Sommige informatie wordt in het Engels weergegeven.
Over mij
Technology is at its best when it simplifies complex processes. I’m Abdul Wasay, a developer with 4+ year experience of turning sophisticated AI, RAG and ML concepts into robust, deployable software. I specialize in complete pipelines — building custom RAG applications, integrating LLMs, training & optimizing reliable ML models, wrapping functionalities in clean backends and seamless deployments. Every pipeline I ship is production-hardened, tested, and built to scale from day one. I ensure that your app runs reliably with on-time delivery. Let's collaborate to build your next AI/ML project! ... Lees meer

Skills

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wasaydelivers
Abdul Wasay
offline • 
Gemiddelde reactietijd: 1 uur

Bekijk mijn diensten

AI-integraties
I will develop a custom rag app and integrate llm like claude gpt
VanafUS$ 90 / projectMeer informatie
Troubleshooting en verbeteringen
I will fix improve customize and deploy your ai vibe coded website
VanafUS$ 10 / projectMeer informatie

Portfolio

Werkervaring

TechBullion

Machine Learning Engineer

TechBullion • Parttime

Apr 2026 - Present • 2 mos

I build end-to-end machine learning systems — from raw, messy data all the way to a live, production-ready API that your application can call in milliseconds. My workflow covers the full ML/MLOps lifecycle: data collection and cleaning, exploratory data analysis (EDA), feature engineering, algorithm selection, model training, hyperparameter tuning, performance optimization, testing, and final deployment — no handoffs, no gaps. On the data side, I work with structured and unstructured sources using Pandas, NumPy, and SQL/NoSQL databases (PostgreSQL, SQLite, Supabase, MongoDB) to ensure your model trains on clean, high-quality data. I use Matplotlib, Seaborn, and Plotly to surface insights and communicate results clearly. For modeling, I work across Scikit-Learn and TensorFlow — regression, classification, clustering, time-series forecasting, NLP, and more. I don't just train a model; I select the right algorithm for your specific problem, validate it rigorously, and fine-tune it until it performs. Then I integrate it. Your model gets wrapped in a production-grade REST API using FastAPI or Flask, containerized with Docker, version-tracked with MLflow, and deployed through automated CI/CD pipelines via GitHub Actions. The result is a model that doesn't just work in a notebook — it works in the real world, reliably, repeatably, and at scale.