You will get NLP | Chatbot | NER | NLTK | Text & Sentiment Analysis | Language Model
Project details
Unlock the power of Natural Language Processing (NLP) with tailored solutions designed for your business. Whether you need sentiment analysis to understand customer feedback, named entity recognition (NER) for structured insights, or advanced applications like chatbots, summarizers, or question-answering systems, I deliver enterprise-grade results.
I specialize in building scalable NLP systems using spaCy, Hugging Face Transformers, PyTorch, and TensorFlow, with seamless integration into your existing workflows. Every project includes rigorous model validation, performance optimization, and production-ready code to ensure your system operates reliably in real-world use cases.
Clients choose me because I combine deep expertise in AI engineering with hands-on deployment experience. From preprocessing pipelines and custom tokenizers to robust chatbot applications, I deliver solutions that are not just prototypes, but scalable, production-ready systems.
Your investment guarantees not only high-quality models but also professional engineering practices (version control, testing, documentation). Let’s transform your text data into actionable intelligence with advanced NLP.
I specialize in building scalable NLP systems using spaCy, Hugging Face Transformers, PyTorch, and TensorFlow, with seamless integration into your existing workflows. Every project includes rigorous model validation, performance optimization, and production-ready code to ensure your system operates reliably in real-world use cases.
Clients choose me because I combine deep expertise in AI engineering with hands-on deployment experience. From preprocessing pipelines and custom tokenizers to robust chatbot applications, I deliver solutions that are not just prototypes, but scalable, production-ready systems.
Your investment guarantees not only high-quality models but also professional engineering practices (version control, testing, documentation). Let’s transform your text data into actionable intelligence with advanced NLP.
Machine Learning Tools
BERT, Chainer, ChatGPT, GitHub Copilot, Google AutoML, GPT-3, Keras, MATLAB, Microsoft CNTK, Microsoft Excel, NLTK, NumPy, OpenCV, Python, PyTorch, R, scikit-learn, SciPy, Scrapy, SQL, TensorFlow, Tesseract OCR, Vertex AI, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$100
|
Standard
$400
|
Advanced
$700
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 25 days |
Number of Revisions | 1 | 2 | 4 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | 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
+$20 - $150
Additional Revision
+$25
Additional Model Variation
(+ 2 Days)
+$50
Additional Scenario
(+ 1 Day)
+$30
Additional Graph/Chart
(+ 1 Day)
+$20
Model Documentation
(+ 3 Days)
+$100
Data Source Connectivity
(+ 3 Days)
+$100
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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 - 4:03 pm 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 Submission
Client purchases project and provides datasets, project goals, and preferred NLP models.
Data preprocessing
Clean, normalize, and tokenize text; handle missing or noisy data.