Machine Learning Engineer

Job description

Purpose & Overall Relevance for the Organization: A Machine Learning Engineer is a specialist who applies its expertise in end-to-end Model Development Lifecycle (MDLC), artificial intelligence and engineering - software, DevOps, data, cloud, and platform; to improve and productionize state of the art machine learning models. They can pivot between data centric (data engineering) or model centric (data science) approaches to enhance predictive model performance and apply various software engineering techniques to deploy and scale models. Key Responsibilities: Analytics: - Builds components for Data platform for distributed data processing pipelines and scalable feature stores including data health monitoring and alerts. - Builds components for ML platform to enable distributed model training and evaluations, including model observability and model performance monitoring - Designs end to end Machine Learning Pipeline (i.e MLOps) - Works with data scientists and data engineers to productionize data pipelines and machine learning models, so that various business requirements can be implemented and scaled - Assists in generating last mile data readiness (for example embeddings) for the...