AI / ML Full Stack Developer

Architect, train, and deploy end-to-end artificial intelligence models and full-stack software applications.

Manipulate, clean, and structure large datasets systematically utilizing Pandas and Numpy execution libraries.

Apply core mathematical models and predictive probability metrics through robust Statistics frameworks.

Design, train, and validate traditional predictive machine learning models using Scikit-Learn tools.

Develop backend analytical modules and custom data manipulation scripts written in Python.

Implement custom supervised and unsupervised ML Algorithms to solve complex engineering problems.

Build deep learning spatial and image recognition pipelines using Convolutional Neural Networks (CNN).

Structure modular, maintainable, and scalable software codebases by applying rigid OOPS concepts.

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related quantitative domains.

3–5 Yrs of dedicated professional software development experience focusing on machine learning systems.

Direct, verifiable practical history demonstrating strong proficiency in Python programming.

Deep conceptual understanding of statistical modeling, object-oriented design patterns, and neural network architectures.

Strong diagnostic and problem-solving capabilities paired with clear technical documentation skills.