Design, build, and implement machine learning (ML) or deep learning (DL) models for predictive analytics, classification, clustering, or recommendation systems.
Collaborate with data engineers and scientists to prepare and process large-scale datasets.
Research and prototype AI solutions for business challenges (e.g., NLP, computer vision, time series, generative AI).
Develop and optimize models using frameworks such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face.
Deploy models into production using MLOps pipelines (e.g., with Docker, Kubernetes, MLflow, SageMaker, or Azure ML).
Monitor model performance, retrain, and tune hyperparameters to ensure reliability and accuracy over time.
Communicate technical findings to stakeholders through reports, dashboards, or visualizations.
Stay current with emerging AI technologies, research papers, and industry trends
