Develop and implement machine learning algorithms for various applications.

Design and build AI models using deep learning frameworks like TensorFlow or PyTorch.

Collect, clean, and preprocess large datasets for AI and ML projects.

Evaluate model performance using appropriate metrics and validation techniques.

Optimize AI models for speed, scalability, and resource efficiency.

Stay updated with the latest advancements in AI, ML, and deep learning.

Collaborate with cross-functional teams to integrate AI solutions into products.

Document AI model development, testing, and deployment processes.

Troubleshoot and debug issues related to AI model performance and deployment.

Conduct research to explore new AI techniques and methodologies.

Present AI project findings and recommendations to stakeholders.

Implement data augmentation techniques to improve model robustness.

Monitor AI model performance in production and retrain as needed.

Crafting AI/ML models using Python and relevant libraries like TensorFlow or PyTorch.

Analyzing large datasets to extract features and insights for model training.

Designing and implementing machine learning algorithms for specific applications.

Training AI/ML models using prepared datasets and optimizing performance.

Deploying models to production environments and monitoring their performance.

Creating new features from existing data to improve model accuracy.

Optimizing code for performance and scalability in AI/ML applications.

Conducting research to develop new AI/ML techniques and methodologies.

Collaborating with cross-functional teams to integrate AI/ML solutions.

Documenting AI/ML models, algorithms, and processes for future reference.

Testing and validating AI/ML models to ensure accuracy and reliability.