Autoencoder dimentionality reduction code with good accuracy

I am looking for a skilled freelancer who can develop an autoencoder dimensionality reduction code with good accuracy using Python.
I have a code for PCA for dimensionality reduction on the same dataset
I need a autoencoder code with fine-tuning which gives good accuracy.

Dataset: I will provide the specific dataset that should be used for testing the code.
Dataset is divided into 6 files
6 files needs to be dimensionality reduction using autoencoder
Don't worry I have sample for that


Accuracy: The desired accuracy level for the model is 80-90%.

Ideal Skills and Experience:
- Strong proficiency in Python programming language
- Experience with developing autoencoder algorithms for dimensionality reduction
- Knowledge of machine learning and deep learning concepts
- Ability to work with large datasets
- Familiarity with data preprocessing and feature engineering techniques
- Strong problem-solving and debugging skills

If you have the required skills and experience, please submit your proposal with relevant examples of your previous work.