Machine Learning Engineer

At Dow, we believe in putting people first and we’re passionate about delivering integrity, respect and safety to our customers, our employees and the planet.   Our people are at the heart of our solutions. They reflect the communities we live in and the world where we do business. Their diversity is our strength. We’re a community of relentless problem solvers that offers the daily opportunity to contribute with your perspective, transform industries and shape the future. Our purpose is simple - to deliver a sustainable future for the world through science and collaboration. If you’re looking for a challenge and meaningful role, you’re in the right place.About you and this role Dow has an exciting and challenging opportunity for a Machine Learning Engineer within our Enterprise Data & Analytics organization located in Houston, TX; Midland, MI; or Champaign, IL.  As a Machine Learning Engineer in our Data & Analytics Platforms team specializing in data and analytics solutions, you will work with a cross-functional team whose objective is to deliver solutions that drive business value for Dow. In this role, you will work closely with data engineers, data scientists, domain experts, and software engineers to design, develop, and deploy machine learning systems, including training and inference pipelines on the Azure Databricks platform. You will also help drive a culture around setting standards and adopting best practices for machine learning and MLOps across the organization.  ResponsibilitiesDesigns and implements pipelines and other workflow infrastructure to meet the requirements for new AI/ML solutions that involve online, batch, or real-time inferenceDeploys and monitors machine learning models in production using Databricks Model Registry, Jobs, and WorkspaceFrequently collaborates with data engineers, DevOps/platform engineers, data scientists, and domain experts as part of a comprehensive MLOps framework to ensure AI/ML solutions are performant, reliable, and maintainableWorks frequently with application development teams to ensure seamless integrationsWorks proficiently with various ML frameworks, such as scikit-learn, TensorFlow, PyTorch, Keras, as well as distributed frameworks like Spark MLlib and RayPerforms data analysis, feature engineering, model selection, hyperparameter optimization, and model evaluation using Databricks MLFlow, Delta Lake, and SQL Analytics and other tools as part of the end-to-end ML lifecycle Researches and implements new machine learning techniques and methods using Databricks, staying abreast of the latest trends and technologiesDocuments and communicates machine learning results and insights to stakeholders using Databricks notebooks and dashboards Understands IT security policies and implements them as part of new solution designs Follows and promotes the best practices and standards for machine learning and MLOps across the organization using Databr...