Midhun Mukundan

About

I’m an AI and Cloud Software Developer passionate about building intelligent, scalable systems that bridge machine learning and real-world applications. With hands-on experience in Python, C++, and Java, I’ve developed and deployed AI-driven cloud solutions using AWS, Docker, Jenkins, and SageMaker, improving efficiency and reliability through automation and optimization. My work spans NLP, computer vision, and deep learning, integrating AI models into practical use cases that enhance performance and user experience. Completed a Master’s in Robotics with AI at London Metropolitan University, I’m driven by curiosity, continuous learning, and the goal of using technology to make meaningful global impact.

Programming Languages

PYTHON 80%
SQL 70%
HTML AND CSS 60%
C++ 50%
RUST 50%
R 40%

Technical Skills

  • Data Structures and Algorithms.
  • Docker, Kubernetes, Terraform, Jenkins
  • Frameworks: Tensorflow, PyTorch, Django, React
  • Common libraries: numpy, pandas, matplotlib, sklearn, OpenCV
  • Cloud Computing: AWS, Amazon Sage maker, GCP
  • Text editors IDE :– VS code, Jupyter Notebook, Google Colab, PyCharm
  • Databases – Postgres, MongoDB
  • Microsoft Excel, Power BI

Education

Master in AI & Robotics

2023 - 2024

London Metropolitan University

Coursework: The design and control of a Cybernetic Hand, Optimal path finding using A* algorithm, Predicting house prices using random forest and logistic regression, published two research papers on ethics and societal impact on AI and Robotics in IEEE.

Bachelor's in Mechanical Engineering

2018 - 2022

SCMS school of Engineering & Technology

Learned Calculus, Differentials, Linear Algebra in semester 2,3 and 4

Professional Experience

AI and Cloud Software Developer

Nov 2023 - Sep 2025

London Metropolitan University, London, UK

    Engineered AI-integrated cloud applications using Python, C++, and Java, achieving up to 40% faster processing through optimized algorithms and resource allocation. Deployed scalable solutions via AWS Lambda, EC2, and SageMaker, improving system uptime by 99.5%. Designed microservices for model deployment and real-time analytics, handling 10K+ requests/day with low latency.Implemented CI/CD pipelines and containerized workflows using Docker and Jenkins, reducing deployment time by 60%.

Software Developer

Sep 2022 - Feb 2023

Infolitz Software Private Limited, Kerala, India

  • Collaborated with the development team to identify, debug, and test Python code, achieving a 90% reduction in identified bugs and significantly improving code stability.
  • Optimized core application features, improving performance by 25% and enhancing code maintainabilty and adherences to best practices.

Projects

Here are some of the notable projects that I have done with their respective code bases on Github

Developed a Real-Time Translation System Using NLP on Raspberry Pi5
  • Fine-tuned a pretrained Helsinki Transformers NLP model to achieve real-time translation between Malayalam and English with low latency.
  • Engineered the system to output translated speech simultaneously through both headphone and speaker connected to a Raspberry Pi.
  • Optimized the translation pipeline to ensure seamless audio playback with minimal delay, enhancing the user experience.
Snake Game using Reinforcement Learning
  • Developed an AI-driven game to optimize agent decision-making and improve gameplay strategies using Reinforcement learning.
Development of a time mapping Software application for improving productivity in the Renault service centre
  • Developed a software application to enhance productivity in automotive workshops by tracking service times through unique QR codes.
  • Contributed to frontend development using HTML and CSS, integrated the database with the backend and built the backend using Django.

Research papers

Here are some of the notable Research papers that i have published on Research Gate

A Bilingual Headphone Translator for Real-Time English and Malayalam Communication Using Raspberry Pi 5

This research paper details the development of a bilingual headphone translator designed for real-time translation between English and Malayalam, utilizing a Raspberry Pi 5 as its core processing unit. The primary objective of this project is to create a portable and efficient solution to overcome language barriers in various social, educational, and professional contexts. The system architecture integrates advanced speech recognition, Natural Language Processing (NLP) models, and text-to-speech synthesis to facilitate seamless communication. Spoken input is captured via a microphone, converted to text, translated, and then synthesized back into speech, with the final audio output delivered simultaneously through headphones and a speaker. This project specifically leverages fine-tuned Transformer-based models, namely the Helsinki-NLP models, to ensure high accuracy in translation, particularly for a low-resource language like Malayalam. The Raspberry Pi 5 was chosen for its compact size, affordability, and processing power, which allows the device to operate as a standalone unit. The final implementation demonstrates the viability of deploying sophisticated NLP models on embedded systems, offering a cost-effective and user-friendly tool with significant potential for broader applications in multilingual environments.

Computer Vision and Legal, social, ethical and professional (LSEP) Issues and Challenges

This paper explores the legal, social, ethical, and professional (LSEP) challenges in computer vision, including privacy, bias, and accountability. It aims to promote responsible and sustainable development of these technologies while addressing societal impacts.

Research Case study: A meta-research on innovative current Trends in Robotics

Robotics has evolved significantly, integrating AI, ML, and emerging trends like soft and swarm robotics to revolutionize industries and daily life. The future promises safer workplaces, better healthcare, and sustainable solutions, necessitating continuous learning and adaptation.