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wasaydelivers

Abdul Wasay

@wasaydelivers

AI Engineer: Specialized in ML and MLOps

Pakistán
Inglés, Urdu
Parte de la información aparece en idioma inglés.
Sobre mí
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! ... Lee más

Habilidades

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wasaydelivers
Abdul Wasay
desconectado • 
Tiempo medio de respuesta: 1 hora

Revisa mis servicios

Integraciones de IA
I will develop a custom rag app and integrate llm like claude gpt
DeUSD 90 / proyectoMás información
Solución de problemas y mejoras
I will fix improve customize and deploy your ai vibe coded website
DeUSD 10 / proyectoMás información

Porfolio

Experiencia laboral

TechBullion

Machine Learning Engineer

TechBullion • Tiempo parcial

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.