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+[Developer Guide](#developer-guide)
+- [Getting Started](#getting-started)
+    - [Fork OpenSearch Remote Vector Index Builder Repo](#fork-remote-vector-index-builder-repo)
+    - [Install Prerequisites](#install-prerequisites)
+        - [Python Dependencies](#python-dependencies)
+- [Python Guide](#python-guide)
+    - [Language Formatting Guide](#language-formatting-guide)
+    - [Testing Guide](#testing-guide)
+- [Building Docker Images](#building-docker-images)
+    - [Faiss Base Image](#faiss-base-image)
+    - [Core Image](#core-image)
+- [Provisioning an Instance for Development](#provisioning-an-instance-for-development)
+- [Memory Profiling](#memory-profiling)
+    - [GPU Memory Profiling with NVIDIA SMI](#gpu-memory-profiling-with-nvidia-smi)
+    - [CPU Memory Profiling with memory_profiler](#cpu-memory-profiling-with-memory_profiler)
+
+# Developer Guide
+
+So you want to contribute code to OpenSearch Remote Vector Index Builder? Excellent! We're glad you're here. Here's what you need to do.
+
+## Getting Started
+
+### Fork Remote Vector Index Builder Repo
+
+Fork [opensearch-project/OpenSearch Remote Vector Index Builder](https://github.com/opensearch-project/remote-vector-index-builder) and clone locally.
+
+Example:
+```
+git clone https://github.com/[username]/remote-vector-index-builder.git
+```
+
+### Install Prerequisites
+
+#### Python Dependencies
+
+The following are commands to install dependencies during local development and testing.
+The required dependencies are installed onto the Docker image during creation.
+
+Core Dependencies:
+```
+pip install -r remote_vector_index_builder/core/requirements.txt
+```
+
+Test Dependencies:
+```
+pip install -r test_remote_vector_index_builder/requirements.txt
+```
+
+## Python Guide
+### Language Formatting Guide
+Run the following commands from the root folder. Configuration of below tools can be found in [`setup.cfg`](setup.cfg).
+
+The code lint check can be run with:
+```
+flake8 remote_vector_index_builder/ test_remote_vector_index_builder/
+```
+
+The formatting check can be run with:
+```
+black --check remote_vector_index_builder/ test_remote_vector_index_builder/
+```
+
+The code can be formatted with:
+```
+black remote_vector_index_builder/ test_remote_vector_index_builder/
+```
+
+### Testing Guide
+The static type checking can be done with:
+```
+mypy remote_vector_index_builder/ test_remote_vector_index_builder/
+```
+The Python tests can be run with:
+```
+pytest test_remote_vector_index_builder/
+```
+
+## Building Docker Images
+The Github CIs automatically publish snapshot images to Dockerhub at [opensearchstaging/remote-vector-index-builder](https://hub.docker.com/r/opensearchstaging/remote-vector-index-builder).
+
+The following are the commands to build the images locally:
+
+### Faiss Base Image
+The [Faiss repository](https://github.com/facebookresearch/faiss/) is added as a submodule in this repository. Run the below command to initialize the submodule first.
+```
+git submodule update --init
+```
+The Faiss base image can only be created on an NVIDIA GPU powered machine with CUDA Toolkit installed.
+
+Please see the section [Provisioning an instance for development](#provisioning-an-instance-for-development) to provision an instance for development.
+
+Run the below command to create the Faiss base image:
+```
+docker build  -f ./base_image/build_scripts/Dockerfile . -t opensearchstaging/remote-vector-index-builder:faiss-base-latest
+```
+
+### Core Image
+The path [`/remote-vector-index-builder/core`](/remote_vector_index_builder/core/) contains the code for core index build functionalities:
+1. Building an Index
+2. Object Store I/O
+
+Build an image with the above core functionalities:
+```
+docker build  -f ./remote_vector_index_builder/core/Dockerfile . -t opensearchstaging/remote-vector-index-builder:core-latest
+```
+
+## Provisioning an instance for development
+
+A NVIDIA GPU powered machine with CUDA Toolkit installed is required to build a Faiss base image and to run the Docker images to build an index.
+
+Typically an [EC2 G5](https://aws.amazon.com/ec2/instance-types/g5/) 2xlarge instance running a Deep Learning OSS Nvidia Driver AMI with Docker CLI installed is recommended for development use.
+
+[Setup an EC2 Instance](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EC2_GetStarted.html)
+
+## Memory Profiling
+
+Simple memory profiling can be done during development to get memory usage statistics during the Index Build process.
+
+### GPU Memory Profiling with NVIDIA SMI
+
+1. Install [py3nvml](https://pypi.org/project/py3nvml/): In [`/remote_vector_index_builder/core/requirements.txt`](/remote_vector_index_builder/core/requirements.txt) add `py3nvml` on a newline.
+
+2. Add import statement and initialize method in the file containing the driver code.
+```
+from py3nvml import nvidia_smi
+nvidia_smi.nvmlInit()
+```
+
+3. Define and call the below method wherever necessary. e.g. before and after calling the GPU index cleanup method.
+```
+from py3nvml import nvidia_smi
+
+def get_gpu_memory():
+    handle = nvidia_smi.nvmlDeviceGetHandleByIndex(0)  # GPU Device ID
+    info = nvidia_smi.nvmlDeviceGetMemoryInfo(handle)
+    print(f"Total: {info.total/1024**2:.2f}MB")
+    print(f"Free: {info.free/1024**2:.2f}MB")
+    print(f"Used: {info.used/1024**2:.2f}MB")
+
+```
+
+### CPU Memory Profiling with memory_profiler
+
+1. Add the below command in [`/remote_vector_index_builder/core/Dockerfile`](/remote_vector_index_builder/core/Dockerfile) to install [memory_profiler](https://pypi.org/project/memory-profiler/).
+```
+RUN conda install -c conda-forge memory_profiler -y
+```
+
+2. In the file that contains the function that needs to be profiled, add the import and an `@profile` annotation on the function.
+```
+from memory_profiler import profile
+
+@profile
+def my_func():
+    a = [1] * (10 ** 6)
+    b = [2] * (2 * 10 ** 7)
+    del b
+    return a
+```