Lead Machine Learning Engineer
of America, Newark, NJ): Responsible for model deployment, algorithm selection, feature engineering, model interpretability, maintenance, and compliance in collaboration with data scientists to help productionize machine learning models at scale. Steer machine learning initiatives from conception to full-scale production. Foster robust relationships with business partners and cross-functional application teams, including DevOps, cloud engineering and platform team. Architect, design, code and deploy machine learning models to cloud environment using preprocessing and training scripts provided by data scientists, ensuring strict adherence to enterprise coding standards. Forge processes, establish model monitoring practices and implement a governance framework to ensure the successful operationalization of models. Deliver essential model training and inference components, frameworks, services using ML Cloud Services ex. AWS Sagemaker. Leverage and optimize end to end model development life cycle (MDLC), Jenkins based CI/CD/CT pipelines, AWS Sagemaker pipeline. Architect and refine training and inference data pipelines, data flow, and data collection strategies for cross-functional teams, assembling extensive and intricate datasets to fulfill business requirements. Collaborate closely with data architects and design teams to resolve technical
