Responsibilities:

Lead and manage a team of software engineers in the development of AI software applications
Set technical direction for the team and ensure that projects are completed on time and within budget
Work with stakeholders to gather requirements and translate them into technical specifications
Review and approve software code
Conduct unit and integration testing
Deploy and maintain software applications
Stay up-to-date on the latest AI technologies and trends

Resonsebilities :

Embedded Systems:

Developed embedded systems for a variety of applications, including medical devices, industrial automation, and transportation systems.
Used a variety of programming languages and tools, including C/C++, Python, and MATLAB.
Worked closely with hardware engineers to design and implement embedded systems.


Data Science:

Developed data science solutions for a variety of business problems, including customer churn prediction, fraud detection, and product recommendation.
Used a variety of machine learning and statistical techniques, including regression, classification, and clustering.
Worked with stakeholders to gather requirements and interpret results.


Software Development:

Developed software applications for a variety of platforms, including desktop, web, and mobile.
Used a variety of programming languages and frameworks, including Java, Python, and React.
Worked with a team of developers to deliver high-quality software on time and within budget.


Python:

Proficient in Python programming language.
Used Python for a variety of tasks, including data analysis, machine learning, and web development.
Developed Python libraries and modules.


GIS Systems:

Worked with GIS (Geographic Information Systems) systems to collect, store, and analyze spatial data.
Used GIS systems to create maps, charts, and other visualizations.
Implemented GIS solutions for a variety of business problems.

Responsbilities :

Data Science:

Developed data science solutions for a variety of business problems, including customer churn prediction, fraud detection, and product recommendation.
Used a variety of machine learning and statistical techniques, including regression, classification, and clustering.
Worked with stakeholders to gather requirements and interpret results.
Built and maintained data pipelines to collect, clean, and store data.
Developed and deployed machine learning models to production.
Communicated results to stakeholders in a clear and concise manner.


Software Development:

Developed software applications for a variety of platforms, including desktop, web, and mobile.
Used a variety of programming languages and frameworks, including Java, Python, and React.
Worked with a team of developers to deliver high-quality software on time and within budget.
Implemented software solutions for a variety of business problems.
Worked with testers to ensure that software applications are bug-free.
Documented software applications so that they are easy to understand and maintain.


Research:

Conducted research in computer vision, machine learning, and OCR.
Developed new algorithms and techniques for these areas.
Published research papers in top academic journals and conferences.
Collaborated with other researchers to advance the state of the art in these areas.
Presented research findings at academic conferences and workshops.


Computer Vision:

Developed computer vision algorithms for a variety of applications, such as object detection, face recognition, and image segmentation.
Worked with large datasets of images and videos to train and evaluate computer vision models.
Deployed computer vision models to production.
Worked with other engineers and scientists to integrate computer vision into real-world applications.


Machine Learning:

Developed machine learning models for a variety of applications, such as fraud detection, customer churn prediction, and product recommendation.
Worked with large datasets of data to train and evaluate machine learning models.
Deployed machine learning models to production.
Worked with other engineers and scientists to integrate machine learning into real-world applications.


OCR:

Developed OCR (optical character recognition) algorithms for a variety of applications, such as extracting text from scanned documents and converting images of text into machine-readable text.
Worked with large datasets of images and text to train and evaluate OCR models.
Deployed OCR models to production.
Worked with other engineers and scientists to integrate OCR into real-world applications.

Software Developer and AI Expert