Machine Learning Lead

Job Description:

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. Skills : Aws Sagemaker, Aws Bedrock, PyTorch, Tensorflow, scikit-learn, statsmodels, pandas, numpy, prophet, darts, optuna, hyperopt, MLOps, AutoML, SQL

We are looking for an experienced and highly skilled Machine Learning Lead to join our team. The ideal candidate will have a robust background in machine learning, with a particular focus on AWS SageMaker, AWS Bedrock, and generative AI solutions. This role involves leading a team of data scientists and machine learning engineers to develop and implement advanced ML models, ensuring the delivery of high-quality, data-driven insights and solutions.

Key Responsibilities: ● 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