Machine Learning Lead - Python/Tensorflow

Job Description : - 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. Qualifications : - Minimum of 7 years of hands-on experience in machine learning and data science roles, with significant experience in leading and managing ML projects. - Proven track record of successfully delivering end-to-end machine learning solutions from concept to production deployment. - Extensive expertise in AWS services such as SageMaker, AWS Bedrock, and other AI/ML tools. - Strong proficiency in Python and familiarity with machine learning libraries such as TensorFlow, PyTorch, and Scikit-Learn. - Experience with MLOps practices, including model monitoring, deployment automation, and CI/CD pipelines. - Demonstrated ability to design and implement scalable and efficient machine learning architectures in cloud environments. - Deep understanding of data engineering, feature engineering, and data preprocessing techniques. - Experience with AutoML, hyperparameter tuning, and model optimization techniques. - Leadership skills with the ability to lead and mentor a team of data scientists and machine learning engineers effectively. (ref:hirist.tech)

Location: noida, IN

Posted Date: 11/24/2024