Data Collection & Processing → Gathering, cleaning, and preparing datasets for machine learning models.
Model Development → Designing, training, and optimizing ML/DL models using frameworks like TensorFlow, PyTorch, or Scikit-learn.
Integration of AI Models → Embedding AI capabilities into software products and business applications.
Experimentation & Research → Testing new AI techniques, improving accuracy, and enhancing system intelligence.
Deployment & Monitoring → Deploying AI models into production and monitoring their performance over time.
Application Development → Designing and developing software systems, APIs, and web/mobile apps.
Backend & Frontend Development → Building both server-side logic and user-friendly interfaces.
Database Management → Storing, retrieving, and managing structured/unstructured data efficiently.
Testing & Debugging → Ensuring software reliability, scalability, and performance.
Collaboration with Cross-Functional Teams → Working closely with data scientists, designers, DevOps engineers, and stakeholders.
