I provide professional development of AI, machine learning, and embedded software solutions with a strong focus on reliability, security, and performance. My goal is to help clients build practical, scalable, and well engineered solutions that can be confidently used in real world environments.

I am a PhD researcher in Computer Science with industry experience in embedded systems and Linux based software development. I work on real world AI and ML problems and help clients convert ideas, research concepts, or raw data into working, well documented solutions. I combine research driven approaches with practical engineering to ensure that solutions are not only accurate but also efficient and maintainable.

I can help with machine learning and deep learning model development, including CNN, RNN, and Transformer based architectures. I support model fine tuning, evaluation, optimization, and deployment for inference. I also build Python based AI and ML pipelines and provide embedded or system level software support when required.

I follow a structured and transparent workflow. I begin by understanding your problem and requirements clearly, then propose a practical solution approach. I deliver clean, readable, and well documented code with regular updates and clear communication throughout the project.

This service is ideal for startups, researchers, and companies looking for reliable AI and ML solutions built with professional engineering standards and long term usability in mind.