Roles and Responsibilities :
- AI Solution Design : Architect, design, and develop end-to-end AI and machine learning solutions addressing complex business problems across multiple domains.
- Model Development & Optimization : Build, train, and optimize machine learning and deep learning models using frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Data Pipeline Management : Work closely with data engineering teams to design efficient data pipelines, ensuring data quality, scalability, and real-time availability.
- Integration & Deployment : Implement and deploy AI models into production using MLOps tools and platforms such as Docker, Kubernetes, MLflow, or AWS Sagemaker.
- Research & Innovation : Stay updated with emerging trends in AI, NLP, computer vision, and generative AI to propose and prototype new solutions.
- Performance Evaluation : Evaluate model performance using relevant metrics and continuously improve models through retraining, hyperparameter tuning, and feedback integration.
- Collaboration : Partner with cross-functional teams including data scientists, software engineers, and product managers to translate AI models into business value.
- Mentorship : Guide junior engineers and data scientists, providing technical direction and ensuring adherence to best practices in AI development.
Skills Required
Python, Tensorflow, Machine Learning, Deep Learning, Natural Language Processing, Neural Networks