Lead the design, development, and deployment of machine learning models and algorithms to solve complex business problems.
● Oversee the end-to-end machine learning lifecycle, including data preprocessing, model training, evaluation, and deployment.
● Utilize AWS SageMaker to build, train, and deploy machine learning models.
● Leverage AWS Bedrock to develop robust and scalable generative AI solutions for various applications.
● Develop and implement generative AI solutions to enhance business processes and customer experiences.
● Implement MLOps practices, including model monitoring, and automation of the training and deployment pipeline.
● Collaborate with cross-functional teams to integrate ML models into production environments and applications.
● Provide technical leadership and mentorship to a team of data scientists and machine learning engineers.
● Communicate complex machine learning concepts and insights to non-technical stakeholders.
● Ensure the integrity and quality of data throughout the machine learning pipeline.
● Stay current with the latest advancements in machine learning, AI, and AWS technologies to continuously improve capabilities.
● SQL analytics integrated with generative AI solutions to deliver refined, data-driven insights for informed decision-making and data integrity