Responsibilities
- Design, develop, and deploy scalable machine learning models to solve real-world business problems and improve decision‑making processes
- Work extensively on data preprocessing, feature engineering, and model optimization to enhance performance and accuracy
- Build and implement advanced algorithms including deep learning, NLP, and predictive analytics solutions
- Collaborate with cross‑functional teams including data scientists, engineers, and product managers to deliver AI‑driven solutions
- Integrate machine learning models into production environments and ensure smooth deployment pipelines
- Monitor, evaluate, and continuously improve model performance using appropriate metrics and feedback loops
- Work with large datasets and distributed computing frameworks to handle complex data challenges efficiently
- Implement automation processes to streamline model training, testing, and deployment
- Ensure data quality, integrity, and governance standards are maintained across all AI workflows
- Research and stay updated with the latest advancements in AI, ML, and data science technologies
- Utilize cloud platforms such as AWS, Azure, or GCP for model deployment and scalability
- Develop APIs and services to expose machine learning functionalities to other applications
- Troubleshoot and resolve technical issues related to model performance and deployment
- Document processes, methodologies, and system designs for future reference and scalability
- Contribute to innovation by identifying new AI opportunities within the organization
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