You will get 🚀 Scalable Data Pipelines for Machine Learning Success
Top Rated
Top Rated
Project details
You will get a scalable and robust data pipeline designed to streamline data ingestion, transformation, and integration. With over 6+ years of experience in Data Engineering and AI, I deliver solutions that empower businesses to harness their data for actionable insights and decision-making.
What you will get:
✅ Custom ETL/ELT Pipelines: Efficient data ingestion, transformation, and storage for seamless analytics.
✅ Cloud Integration: Deployment on leading platforms like Azure, AWS, or GCP for real-time scalability.
✅ Optimized Data Architecture: Scalable data lakes or warehouses tailored to your business requirements.
✅ Comprehensive Documentation: Easy-to-understand technical documentation for maintenance and handover.
✅ Testing & Validation: Ensured performance, reliability, and accuracy of the pipeline.
Transform your raw data into actionable insights with an expertly crafted solution that grows with your business. Let’s get started!
What you will get:
✅ Custom ETL/ELT Pipelines: Efficient data ingestion, transformation, and storage for seamless analytics.
✅ Cloud Integration: Deployment on leading platforms like Azure, AWS, or GCP for real-time scalability.
✅ Optimized Data Architecture: Scalable data lakes or warehouses tailored to your business requirements.
✅ Comprehensive Documentation: Easy-to-understand technical documentation for maintenance and handover.
✅ Testing & Validation: Ensured performance, reliability, and accuracy of the pipeline.
Transform your raw data into actionable insights with an expertly crafted solution that grows with your business. Let’s get started!
Machine Learning Tools
Amazon SageMaker, Apache Spark, Azure Machine Learning, Databricks Platform, Google AutoML, MLflow, NumPy, pandas, Python, SQLWhat's included
| Service Tiers |
Starter
$500
|
Standard
$1,200
|
Advanced
$2,000
|
|---|---|---|---|
| Delivery Time | 5 days | 8 days | 12 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 1 | 2 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 0 | 2 | 3 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | |||
Source Code | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$200 - $500Frequently asked questions
32 reviews
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MA
Marya A.
Feb 16, 2026
Internal Knowledge RAG Assistant (Notion, Docs, PDFs → GPT‑4)
Salman understood exactly what we needed and built the system the right way. Everything works smoothly, and we’re really happy with the result.
MA
Marya A.
Jan 30, 2026
Full-Scale AI Automation System for Support, CRM & Internal Operations
Salman completely transformed how we work. Our support tickets have dropped way down, and our CRM now talks perfectly to all our internal tools. Thank you
NA
Najeeb A.
Dec 31, 2025
Knowledge RAG Assistant (Notion, Docs, PDFs → GPT‑4)
The knowledge assistant is incredibly accurate. It saved hours of internal back‑and‑forth. Salman handled everything professionally.
MA
Marya A.
Dec 29, 2025
Structured LLM Ticket Classification with Light RAG
He worked responsibly, avoided making things up, and delivered clear, well structured LLM outputs with strong ethical judgment.
IC
Ikenna C.
Dec 24, 2025
AI-driven features for logistics mobile app
About Muhammad Salman
RAG & LLM Automation Engineer | GPT-4, Claude, LangChain, LangGraph
100%
Job Success
Lahore, Pakistan - 2:31 pm local time
knowledge assistant that answers questions from a company's Notion pages, training manuals,
SOPs and PDFs through GPT-4: $10,200, and the client wrote Salman understood exactly what
we needed and built the system the right way.
Most of my work now looks like that. A second knowledge assistant got this review: The
knowledge assistant is incredibly accurate. It saved hours of internal back and forth. An
automation system I built around a company's support desk and CRM got Our support tickets
have dropped way down, and our CRM now talks perfectly to all our internal tools.
Since December 2024 I have earned about $31,600 across 21 Upwork contracts, nearly all
rated 5.0. Besides the knowledge assistants, that includes an enterprise RAG bot on Azure
OpenAI and Azure Cognitive Search, structured LLM ticket classification, custom GPTs
embedded in a client's course platform, GPT fine tuning on legal-domain data, and a chatbot
that generates t-shirt mockups from a customer's logo. One client hired me to teach him
LangChain and LangGraph for an hour a day. I take that as evidence I can explain this stack,
not just use it.
Right now I am building two systems: an n8n AI workflow buildout, and a multi-tenant SaaS
platform where Claude reads GoHighLevel customer conversations, extracts order details and
generates quotes with garment mockups.
Before the LLM work I did the plumbing that AI projects sit on: ETL pipelines, AI-driven
processing across 863 datasets, and AWS infrastructure for a SaaS deployment. It means I can
take a project from raw data to a deployed system without handing pieces off.
The review I value most is not a 5.0 star count: He worked responsibly, avoided making
things up, and delivered clear, well structured LLM outputs with strong ethical judgment.
With LLM systems, that is the actual job.
If you need a knowledge assistant over your documents, an automation that connects an LLM to
the tools you already run, or an AI feature built properly inside your product, send me the
details and I will tell you how I would build it.
Steps for completing your project
After purchasing the project, send requirements so Muhammad Salman can start the project.
Delivery time starts when Muhammad Salman receives requirements from you.
Muhammad Salman works on your project following the steps below.
Revisions may occur after the delivery date.
Project Kickoff & Requirements Gathering
I will review your goals, datasets, and cloud preferences to align on project expectations and deliverables.
Data Pipeline Development
Build and implement ETL/ELT pipelines to ingest, clean, and transform data based on requirements.