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$
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I will build ai ml solutions computer vision AWS cloud ocr deep learning models
Eesa
About this gig
Looking for a reliable AI/ML developer who delivers production-ready solutions?
You're in the right place.
I specialize in building end-to-end machine learning and deep learning systems, computer vision applications using OpenCV and YOLO, intelligent NLP solutions, and scalable deployments on AWS cloud so your AI actually works in the real world.
What I Build For You:
- Custom ML models classification, regression, clustering, recommendation systems
- Computer vision object detection, face recognition, image segmentation, tracking
- NLP & LLM integration chatbots, sentiment analysis, text summarization, RAG pipelines
- AWS deployment SageMaker, Lambda, EC2, S3, API Gateway, Docker
- MLOps pipelines model training, versioning, monitoring, CI/CD
- Data science & analysis EDA, feature engineering, visualization, dashboards
Tech Stack:
Python · TensorFlow · PyTorch · Scikit-learn · OpenCV · Hugging Face · LangChain · AWS (SageMaker, Lambda, EC2, S3) · Docker · FastAPI · Flask · PostgreSQL · MongoDB
Get to know Eesa
Eesa
- FromPakistan
- Member sinceMar 2025
- Avg. response time1 hour
Languages
Urdu, Pashto, English
I am an AWS cloud architect and full-stack engineer with deep expertise in designing, deploying, and optimizing cloud-native solutions. My core strengths include serverless architectures (Lambda, API Gateway), containerized workloads (ECS, EKS, Fargate), machine learning workflows (SageMaker, Glue, Step Functions), and Node.js backend development. I integrate any database — relational or NoSQL — seamlessly into your AWS environment. I deliver production-ready, secure, and cost-optimized infrastructure as code so your team can maintain and scale with confidence.
My Portfolio
FAQ
Can you work with my existing codebase?
Yes! I can integrate AI/ML models into your existing Python, Node.js, or cloud-based stack. Just share your repo or describe your setup and I'll advise on the best approach.
Do you deploy models to production / cloud?
Absolutely. AWS is my primary cloud — SageMaker for model hosting, Lambda for serverless inference, EC2 for heavier workloads. I can also work with GCP and Azure on request.
How do I know if my project is feasible?
Message me first with a description of your goal. I'll give you a free honest assessment — including what's achievable, realistic timelines, and whether your data is sufficient.
