Generative AI Engineer

Key Responsibilities – AI/ML Engineer

• Design, develop, train, and optimize Machine Learning models using Python, Java, or C++.
• Build and implement AI/ML solutions using TensorFlow, PyTorch, and Scikit-learn.
• Perform data preprocessing, exploratory data analysis, and feature engineering using Pandas, NumPy, and related libraries.
• Apply strong knowledge of algorithms, data structures, and computational complexity to develop efficient and scalable solutions.
• Deploy, monitor, and maintain ML models in production environments using Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP.
• Collaborate with DevOps and engineering teams to build reliable, scalable, and secure ML deployment pipelines.
• Work with SQL and NoSQL databases for data extraction, storage, processing, and analysis.
• Follow software engineering best practices, including version control, code reviews, testing, and documentation.
• Participate in Agile ceremonies, sprint planning, technical discussions, and continuous improvement initiatives.
• Communicate technical findings and AI/ML concepts effectively to cross-functional teams and business stakeholders.