You will get Machine Learning, Deep Learning, Data Science, Data visualization
Project details
Are you looking to turn raw data into actionable insights using state-of-the-art machine learning? I offer end-to-end ML solutions, including data preprocessing, feature engineering, model selection, training, tuning, evaluation, and deployment-ready code. Whether you need classification, regression, clustering, or recommendation systems, I build models that are optimized, interpretable, and production-ready.
With hands-on expertise from Machine Learning and real-world project deployments, I use industry best practices and tools like Scikit-learn, XGBoost, LightGBM, TensorFlow, and PyTorch. I also ensure code reproducibility and provide clear documentation, version control, and consultation.
Perfect for startups, researchers, and product teams looking to implement machine learning workflows that drive measurable impact. Let’s bring your data to life with precision, scalability, and innovation.
With hands-on expertise from Machine Learning and real-world project deployments, I use industry best practices and tools like Scikit-learn, XGBoost, LightGBM, TensorFlow, and PyTorch. I also ensure code reproducibility and provide clear documentation, version control, and consultation.
Perfect for startups, researchers, and product teams looking to implement machine learning workflows that drive measurable impact. Let’s bring your data to life with precision, scalability, and innovation.
Machine Learning Tools
Apache Spark, Apache Spark MLlib, Azure Machine Learning, BERT, Chainer, ChatGPT, Databricks Platform, Keras, Kubeflow, MATLAB, MLflow, NLTK, NumPy, NVIDIA AI Platform, Open Neural Network Exchange, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, SciPy, SQL, Tableau, TensorFlow, Vertex AIWhat's included
| Service Tiers |
Starter
$300
|
Standard
$1,000
|
Advanced
$3,000
|
|---|---|---|---|
| Delivery Time | 7 days | 15 days | 20 days |
Number of Revisions | 2 | 3 | 4 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 2 | 4 | 5 |
Number of Graphs/Charts | 2 | 3 | 1 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | |||
Source Code |
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JS
Joanne Da S.
Feb 27, 2024
Looking for C, MicroPython developer
AY
Alex Y.
Sep 18, 2023
Inverter
JS
Joanne Da S.
May 22, 2023
Looking for C, MicroPython developer
Great developer. Actually going to hire again right away
MP
Morgan P.
May 18, 2023
MicroPython Porting Engineer
Had an outstanding experience with this freelancer. He was fast, prompt, and effective, completely solving my problem immediately. Very very grateful to Zain.
Kd
Kasun d.
Nov 29, 2022
Conceptual System Level Paper Design of a Car-Mounted Solar Cell and Wind Generator charger
2nd time with him. Did a very good Job
About Zain
Senior AI Engineer | RAG | LangChain | AI Agents | Agentic AI | LLMOPs
100%
Job Success
Ubauro, Pakistan - 4:06 am local time
⭐️ 56+ completed projects spanning full-stack, machine learning, and generative AI.
⭐️ 16 end-to-end projects: RAG, multimodal RAG, Agentic AI systems, vision-language fine-tuning
Most AI projects stall in the gap between a working notebook and something you can actually ship and maintain — no clean deployment path, no way to evaluate or monitor it.
Closing that gap is my focus.
I'm Zain — a generative AI application engineer. Not just the model. The entire stack:
✅ Agent Orchestration ✅ RAG pipeline ✅ Fine-tuned LLM
✅API ✅ containerization and Kubernetes deployment ✅ CI/CD pipeline
✅ Monitoring and observability that keeps it all healthy at scale.
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WHAT I BUILD FOR YOU
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🔷 RAG & agents — semantic search, reranking, memory, and multi-agent workflows with LangChain, LangGraph, and CrewAI over FAISS, Qdrant, Pinecone, and AstraDB.
🔷 Fine-tuning — adapting open vision-language and language models (LoRA / QLoRA / PEFT / SFT) to your data and domain, efficiently enough to train on accessible hardware.
🔷 Deployment & MLOps — Docker, Kubernetes, FastAPI, GitHub Actions CI/CD, Terraform, and AWS, with Prometheus / Grafana monitoring and LLM-specific tracing via Langfuse. Your AI ships reliably, scales automatically, and is observable from day one.
🔷 Multimodal systems — pipelines that combine text, PDFs, images, and audio using OCR, vision-language models (CLIP, Qwen2-VL, Florence-2, MAIRA-2), and Whisper.
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WHO I WORK BEST WITH
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→ SMBs, funded startups, and agencies who need someone who can both build a GenAI feature and get it deployed — a builder who ships, not just a notebook.
→ CTOs and technical founders who need a senior AI partner, not just a developer
I do not take every project. I take projects where I can make a real difference — where the work is technically meaningful and the client is serious about building something that lasts.
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TECH STACK
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✅ Languages: Python · SQL · Shell · YAML · Rust
✅ LLMs & GenAI: OpenAI GPT · Claude · Gemini · LLaMA · Mistral · Hugging Face
✅ RAG & Agents: LangChain · LangGraph · LlamaIndex · Multimodal RAG
✅ Fine-Tuning: LoRA · QLoRA · SFT · DPO · RLHF
✅ Inference: vLLM · TGI · Quantization (GGUF · AWQ · GPTQ)
✅ Vector DBs: FAISS · ChromaDB · Pinecone · Weaviate. LanceDB
✅ ML/DL: PyTorch · TensorFlow · Scikit-Learn · Keras · OpenCV
✅ Backend: FastAPI · Flask · Django
✅ Databases: PostgreSQL · MySQL
✅ Cloud: AWS (EC2 · EKS · SageMaker · Fargate · ECR)
✅ Containers & Orchestration: Docker · Kubernetes · Helm
✅ Infrastructure as Code: Terraform · Ansible
✅ CI/CD: Jenkins · GitHub Actions · GitLab CI/CD · ArgoCD · CircleCI
✅ Monitoring: Prometheus · Grafana · ELK Stack · Langfuse
✅ Experiment Tracking: MLflow · Weights & Biases · DVC
✅ Version Control: Git · GitHub · GitLab
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If you are building an AI system that needs to actually work in production — not just in a notebook — I would like to hear about it.
Send me a message with what you are building, and I will tell you honestly whether I can help and how.
Steps for completing your project
After purchasing the project, send requirements so Zain can start the project.
Delivery time starts when Zain receives requirements from you.
Zain works on your project following the steps below.
Revisions may occur after the delivery date.
Client purchases the project and shares requirements
I’ll review your data, use case, and project goals to align the solution with your expectations.
Model Selection & Training
Choose appropriate machine learning algorithms (e.g., regression, classification, clustering). Train the model using proven techniques like cross-validation and hyperparameter tuning.