Syed Mehdi
Syed MehdiSyed MehdiAI Engineer · Good things takes time.

I build AI that
reaches production.

Applied AI & systems engineer. RAG, computer vision, and ML pipelines engineered, deployed, and maintained. Backed by enterprise IT and an MSc in AI.

[ MSc AI ]   [ RAG · Vision · MLOps ]   [ Production-first ]
// about

From the engine room of enterprise IT to building AI that ships.

Most AI engineers never touched production infrastructure. I started there firewalls, Active Directory, servers, then took an MSc in AI into RAG, anomaly detection, and computer vision. The operator’s instinct stayed: a model that can’t deploy and survive real data isn’t finished.

MSc
Artificial Intelligence
0%
Production-focused
Portrait
◦ live presence
Syed Mehdi
United Arab Emirates
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LangChainLangGraphAutoGenRAGLLMOpsHugging FacePyTorchTensorFlowComputer VisionFastAPIDockerKubernetesAWSAzureChromaDBpgvectorPrompt EngineeringMLOpsCI/CDPython
// selected work
All projects →
01Customer Support AI Agent with RAG & LLMOpsAI
02Fraud Detection with LSTM AutoencoderAI
03Mental Health AI ChatbotAI
04Plant Disease DetectionAI
// work with me

How I can help

Everything I offer →
AI

AI / LLM Engineering

RAG systems, agents, and LLM products built to deploy.

~ 2 to 4 weeks
  • +RAG pipeline architecture + deployment
  • +LLM agent development (LangChain / LangGraph)
  • +FastAPI backend + Docker containerisation
View details →
Most Requested | Customised

AI Training & Mentorship

Learn Artificial Intelligence from Beginner to Expert

4-stage path · ~ 10 to 15 days
  • +Introduction to AI & Machine Learning
  • +Python Programming for AI Applications
  • +Deep Learning & Neural Networks
View details →
Custom

ML Engineering & MLOps

Models that survive contact with real, messy data.

~ 3 to 6 weeks
  • +Predictive modelling + anomaly detection
  • +Computer vision pipelines (transfer learning)
  • +AWS Lambda / Azure ML deployment
View details →
// research lab

Open questions

Explore →
ongoing35%

Compliance-Aware ML for AIOps

Formalising patterns for governance and compliance inside applied ML operations.

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Let's build
something precise.

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