You will get a research-grade AI/ML prototype developed from idea to deployment
Project details
You will get a research-grade AI/ML prototype developed from your idea, dataset, research paper, or technical problem.
I can help you move from a rough concept to a working machine learning solution by designing the experiment, selecting a suitable model, implementing the pipeline, evaluating the results, and explaining the findings clearly.
Depending on the package, this may include:
• AI/ML feasibility analysis
• Dataset review and preprocessing strategy
• Baseline model development
• PyTorch or scikit-learn implementation
• Model training and evaluation
• Metrics, plots, and error analysis
• Technical summary or experiment report
• Deployment-ready demo using FastAPI, Streamlit, or Docker
The premium package is designed for clients who want more than a notebook. You will receive a working prototype that can be demonstrated, tested, and used as a foundation for further product development.
I can help you move from a rough concept to a working machine learning solution by designing the experiment, selecting a suitable model, implementing the pipeline, evaluating the results, and explaining the findings clearly.
Depending on the package, this may include:
• AI/ML feasibility analysis
• Dataset review and preprocessing strategy
• Baseline model development
• PyTorch or scikit-learn implementation
• Model training and evaluation
• Metrics, plots, and error analysis
• Technical summary or experiment report
• Deployment-ready demo using FastAPI, Streamlit, or Docker
The premium package is designed for clients who want more than a notebook. You will receive a working prototype that can be demonstrated, tested, and used as a foundation for further product development.
Machine Learning Tools
Amazon SageMaker, BERT, ChatGPT, Databricks Platform, Databricks MLflow, GitHub Copilot, Google Data Studio, Google Sheets, NLTK, NumPy, NVIDIA AI Platform, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, Sonnet, TensorFlow, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$100
|
Standard
$500
|
Advanced
$900
|
|---|---|---|---|
| Delivery Time | 7 days | 21 days | 45 days |
Number of Revisions | 1 | 2 | 2 |
Number of Model Variations | 0 | 1 | 2 |
Number of Scenarios | 1 | 2 | 2 |
Number of Graphs/Charts | 2 | 3 | 5 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | - | |
Source Code | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$100 - $500
Additional Revision
+$25
Additional Model Variation
(+ 3 Days)
+$25
Additional Scenario
(+ 3 Days)
+$30
Additional Graph/Chart
+$5About Amin
AI / ML Developer & Researcher | Vision, NLP, Speech
Lahore, Pakistan - 12:34 pm local time
With 4+ years of experience as a Machine Learning Engineer and Researcher, I specialize in developing, training, evaluating, and deploying AI models for both academic and applied research. I can support projects from early experimentation and literature review to reproducible pipelines, API integration, and production-ready deployment.
My primary areas of expertise include:
1️⃣ **AI for Healthcare & Biomedical Imaging**
Developing computer vision and deep learning models for pathology, radiology, histopathology, classification, segmentation, biomarker prediction, and diagnostic research.
2️⃣ **LLMs, NLP & Speech AI**
Building and fine-tuning transformer-based models for natural language processing, speech recognition, retrieval-augmented generation (RAG), conversational AI, and domain-specific language applications.
3️⃣ **Generative AI & Diffusion Models**
Working with modern generative models including diffusion and flow-based architectures for image generation, editing, reference-guided synthesis, and multimodal AI research.
💡 **Core Areas of Expertise**
🔹 Deep learning model development and training: PyTorch, TensorFlow, Hugging Face
🔹 Computer vision and medical imaging research
🔹 LLM fine-tuning, evaluation, RAG, and prompt engineering
🔹 Speech processing and ASR systems
🔹 Diffusion models, generative AI, and image synthesis
🔹 Dataset preparation, experimentation, ablation studies, and error analysis
🔹 Model deployment, API development, and production-oriented AI pipelines
🔹 Academic writing, literature reviews, methodology development, and technical documentation
✅ **Why Choose Me**
🔹 Strong blend of research expertise and practical AI engineering
🔹 Experience spanning healthcare AI, language models, speech AI, and generative models
🔹 Ability to support academic publications, research projects, and production-oriented AI initiatives
🔹 End-to-end support from problem formulation, experimentation, and model development to deployment and documentation
🔹 Focus on reproducible workflows, clean evaluation, and real-world usability
Whether it is developing a medical imaging model, fine-tuning an LLM, improving an ASR pipeline, experimenting with state-of-the-art diffusion models, or deploying an AI prototype into a usable application, I focus on building systems that are technically rigorous, well-evaluated, and aligned with real-world objectives.
Best regards,
Amin Q.
Steps for completing your project
After purchasing the project, send requirements so Amin can start the project.
Delivery time starts when Amin receives requirements from you.
Amin works on your project following the steps below.
Revisions may occur after the delivery date.
Review project goal and requirements
I will review your project idea, available data, expected deliverable, and any sample files or references you provide. If needed, we can clarify the scope before development begins.
Plan the AI/ML approach
I will define the technical approach, including the data preparation strategy, model direction, evaluation method, and expected workflow for the selected package.