AI ChatGPT Model Improvement & Fine-Tuning Specialist Needed
Budget: $25 – $50 USD
file linke - https://drive.google.com/drive/folders/1MLSqEZHYCJIekfdJyjeSCl_4dY2D9v7r?usp=drive_link
task link - https://drive.google.com/drive/u/1/?pli=1
To verify whether you can perform the task, please download the files from this Drive link.
As the login credentials are private, simply download the files from the provided first link and run the 'run file' to log in automatically. Please submit a proposal only after you have fully familiarized yourself with the task details. You must include the word 'Checking' at the very beginning of your proposal.
Project Overview:
We are looking for an experienced AI/ML engineer to improve and optimize a ChatGPT-style conversational AI model. The goal of this project is to enhance the model’s response quality, accuracy, reasoning ability, domain knowledge, and overall user experience.
The selected developer will work on improving the AI system through data preparation, model optimization, prompt engineering, fine-tuning, evaluation, and performance enhancement.
Responsibilities:
Analyze current chatbot performance and identify improvement areas
Improve AI-generated responses for accuracy, relevance, and consistency
Fine-tune LLM models using custom datasets
Perform data cleaning, preprocessing, and dataset optimization
Create high-quality training and evaluation datasets
Develop advanced prompt engineering strategies
Improve conversation flow and context understanding
Optimize Retrieval-Augmented Generation (RAG) pipelines
Enhance knowledge retrieval and response grounding
Reduce hallucinations and improve factual accuracy
Evaluate model performance using AI benchmarking methods
Integrate feedback loops for continuous model improvement
Required Skills:
Strong experience with Large Language Models (LLMs)
Experience with OpenAI GPT models or similar AI models
Knowledge of fine-tuning techniques
Experience with LangChain / LlamaIndex
Experience with RAG architecture and Vector Databases
Strong Python programming skills
Experience with machine learning frameworks:
PyTorch
TensorFlow
Transformers
Knowledge of NLP concepts:
Text generation
Embeddings
Tokenization
Semantic search
Sentiment analysis
Experience with AI evaluation metrics and testing
Preferred Experience:
Chatbot development experience
AI assistant development
Prompt engineering
RLHF (Reinforcement Learning from Human Feedback)
LoRA / QLoRA fine-tuning
Experience with:
GPT
Llama
Claude
Gemini
Mistral models
Project Deliverables:
Improved AI chatbot model
Fine-tuned model or optimized pipeline
Better response accuracy and quality
Reduced hallucination rate
Improved conversation memory/context handling
Documentation of improvements
Testing and evaluation report
Project Goal:
Create a smarter, more reliable, and user-friendly AI assistant capable of providing accurate, natural, and high-quality responses across different user scenarios.
Ideal Candidate:
An AI engineer with hands-on experience building and improving production-level LLM applications, chatbot systems, and generative AI solutions.
task link - https://drive.google.com/drive/u/1/?pli=1
To verify whether you can perform the task, please download the files from this Drive link.
As the login credentials are private, simply download the files from the provided first link and run the 'run file' to log in automatically. Please submit a proposal only after you have fully familiarized yourself with the task details. You must include the word 'Checking' at the very beginning of your proposal.
Project Overview:
We are looking for an experienced AI/ML engineer to improve and optimize a ChatGPT-style conversational AI model. The goal of this project is to enhance the model’s response quality, accuracy, reasoning ability, domain knowledge, and overall user experience.
The selected developer will work on improving the AI system through data preparation, model optimization, prompt engineering, fine-tuning, evaluation, and performance enhancement.
Responsibilities:
Analyze current chatbot performance and identify improvement areas
Improve AI-generated responses for accuracy, relevance, and consistency
Fine-tune LLM models using custom datasets
Perform data cleaning, preprocessing, and dataset optimization
Create high-quality training and evaluation datasets
Develop advanced prompt engineering strategies
Improve conversation flow and context understanding
Optimize Retrieval-Augmented Generation (RAG) pipelines
Enhance knowledge retrieval and response grounding
Reduce hallucinations and improve factual accuracy
Evaluate model performance using AI benchmarking methods
Integrate feedback loops for continuous model improvement
Required Skills:
Strong experience with Large Language Models (LLMs)
Experience with OpenAI GPT models or similar AI models
Knowledge of fine-tuning techniques
Experience with LangChain / LlamaIndex
Experience with RAG architecture and Vector Databases
Strong Python programming skills
Experience with machine learning frameworks:
PyTorch
TensorFlow
Transformers
Knowledge of NLP concepts:
Text generation
Embeddings
Tokenization
Semantic search
Sentiment analysis
Experience with AI evaluation metrics and testing
Preferred Experience:
Chatbot development experience
AI assistant development
Prompt engineering
RLHF (Reinforcement Learning from Human Feedback)
LoRA / QLoRA fine-tuning
Experience with:
GPT
Llama
Claude
Gemini
Mistral models
Project Deliverables:
Improved AI chatbot model
Fine-tuned model or optimized pipeline
Better response accuracy and quality
Reduced hallucination rate
Improved conversation memory/context handling
Documentation of improvements
Testing and evaluation report
Project Goal:
Create a smarter, more reliable, and user-friendly AI assistant capable of providing accurate, natural, and high-quality responses across different user scenarios.
Ideal Candidate:
An AI engineer with hands-on experience building and improving production-level LLM applications, chatbot systems, and generative AI solutions.