You will get Custom AI Model Fine-Tuning, RAG Optimization & LLM Performance Tuning
Project details
I specialize in Optimizing LLM Performance through advanced Fine-Tuning (LoRA/QLoRA) and High-Precision RAG Architecture. Moving beyond basic API calls, I help businesses reduce "Hallucinations" and slash "Inference Costs" by tailoring open-source models (like Llama 3 or Mistral) to their specific domain. Drawing from my work with Stanford researchers on specialized EdTech models, I engineer the data pipelines and vector embedding strategies required to give your AI "Internal Subject Matter Expertise."
What sets my approach apart is a focus on Production Stability and MLOps. Leveraging the same technical rigor I used for Quantic AI and PayRemit, I implement automated Evaluation Frameworks (using RAGAS or TruLens) to measure model accuracy, latency, and drift in real-time. Whether you need to fine-tune a model for private data or optimize a Vector Database for a high-concurrency platform, I provide the deep-learning expertise to ensure your AI is fast, reliable, and cost-effective. Every project includes full Source Code and Model Documentation, ensuring your internal team can maintain the system as your data scales.
What sets my approach apart is a focus on Production Stability and MLOps. Leveraging the same technical rigor I used for Quantic AI and PayRemit, I implement automated Evaluation Frameworks (using RAGAS or TruLens) to measure model accuracy, latency, and drift in real-time. Whether you need to fine-tune a model for private data or optimize a Vector Database for a high-concurrency platform, I provide the deep-learning expertise to ensure your AI is fast, reliable, and cost-effective. Every project includes full Source Code and Model Documentation, ensuring your internal team can maintain the system as your data scales.
Machine Learning Tools
BERT, Keras, Kubeflow, MLflow, NLTK, NVIDIA AI Platform, PyTorch, Stanford CoreNLP, TensorFlow, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$500
|
Standard
$1,250
|
Advanced
$2,000
|
|---|---|---|---|
| Delivery Time | 5 days | 14 days | 30 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 5 |
Number of Scenarios | 2 | 5 | 10 |
Number of Graphs/Charts | 0 | 3 | 10 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code | - |
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AZ
Angela Z.
Jan 26, 2026
AI Chatbot for Telegram
Basil Jilani is an excellent freelancer very professional, responsive, and technically strong. He delivered a stable Telegram AI chatbot with clean code and smooth deployment. Communication was clear throughout, and he understood requirements quickly. Highly recommended I’d definitely work with him again.
RW
Rachel W.
Jan 26, 2026
Senior Python Developer – AI Document Schema Discovery & Extraction
Basil Jilani delivered outstanding work on this project. He showed deep expertise in Python and LLM-based document extraction, implemented clean architecture, and handled schema discovery with impressive accuracy. Communication was clear, timelines were respected, and the final solution was robust and production-ready. Basil is truly a high-level engineer highly recommended for complex AI backend projects.
JM
John M.
Jan 26, 2026
AI Voice Web App MVP (Next.js + Python)
Basil Jilani was awesome to work with fast, reliable, and highly skilled. He delivered the Voicelyt MVP smoothly, handled Next.js + Python integration perfectly, and made smart product decisions to keep things lean and on track. Communication was excellent and everything was production-ready. Highly recommended I’d gladly work with Basil again.
About Basil
Data Analyst | Excel & Sheets Dashboards + Python Data Cleaning
100%
Job Success
Sydney, Australia - 6:07 pm local time
I specialise in two things:
Excel & Google Sheets dashboards: If you have sales data, KPIs, inventory numbers, or any business data sitting in spreadsheets, I'll build you a clean dashboard that updates automatically and actually answers your questions. No more digging through tabs to find what you need.
Survey data analysis & reporting: If you've run a survey (customer feedback, employee engagement, market research, academic study) and now have hundreds or thousands of responses to make sense of, I'll clean the data, run the analysis, and deliver a clear report with the insights that matter.
My edge: I use Python (pandas) behind the scenes to handle large or messy datasets that pure-Excel freelancers struggle with — then deliver the final dashboard or report in the tool you actually want to use (Excel, Google Sheets, Looker Studio, or PDF report).
What you get when you work with me:
• Dashboards that are easy to read and easy to update, not over-engineered
• Honest communication, I'll tell you upfront if something won't work or will take longer than expected.
• Fast turnaround, I'm available 30+ hours a week and respond within a few hours
• Clear documentation so you can use what I build without coming back to me every time
Tools I use: Excel (formulas, pivot tables, Power Query), Google Sheets (including Apps Script for automation), Python with pandas for heavier data cleaning, SQL when needed, Looker Studio for connected dashboards.
About me: I'm completing a Bachelor's in Business Analytics at Macquarie University, which means I bring both the technical side (cleaning, building, automating) and the analytical side (knowing what questions to ask of the data and how to present findings clearly).
If you have data that needs to make sense, send me a message describing what you're working with and what you'd like to get out of it. I'll tell you honestly whether I can help and how I'd approach it.
Steps for completing your project
After purchasing the project, send requirements so Basil can start the project.
Delivery time starts when Basil receives requirements from you.
Basil works on your project following the steps below.
Revisions may occur after the delivery date.
Data Synthesis & Cleaning
I perform exploratory data analysis (EDA) on your dataset to identify biases or inconsistencies. I then format the data for fine-tuning, ensuring high-quality input-output pairs that reinforce the specific domain knowledge required.
Hyperparameter & LoRA Configuration
Using the PEFT (Parameter-Efficient Fine-Tuning) library, I configure the LoRA/QLoRA parameters. This allows us to fine-tune massive models like Llama 3 on consumer-grade or mid-tier hardware, significantly reducing your compute costs.