First American Financial - Dallas, TX
posted about 2 months ago
At CoreLogic, we are driven by a single mission—to make the property industry faster, smarter, and more people-centric. As an IT Analytics Engineer, you will be at the forefront of this mission, exploring a wide range of next-gen technologies including cloud-native applications, machine learning (ML), AI, GenAI, Vision, and Imagery analytics. Our products influence the industry with financial, property, and consumer information, utilizing data analytics along with business intelligence to simplify experiences and bring insights to our customers. We are constantly developing innovative solutions that make the real estate ecosystem smarter, more connected, and more efficient. In this role, you will design robust cloud solutions in Google Cloud Platform that will service CoreLogic's intelligence and data solutions. You will develop and deploy models and services in a managed Kubernetes Framework (Anthos) and enhance the performance of containerized applications. Your responsibilities will also include developing and deploying batch predictions using Dataflow, KFP, and Vertex AI, as well as GenAI models using LangChain. You will demonstrate expertise in Agile methodologies, focusing on backlog management and sprint planning to ensure efficient project progression and delivery. Collaboration is key in this position; you will work cross-functionally with other machine learning engineers and data scientists to drive requirements and create new models. You will implement and maintain ongoing prediction pipelines using tools like Kubernetes, Airflow, KFP, and Vertex AI, ensuring best practices in ML engineering, including code quality, testing, and documentation. Additionally, you will foster a culture of innovation, continuous learning, and knowledge sharing within the team, while understanding and championing the Software Development Life Cycle (SDLC) and the Model Development Life Cycle (MDLC). Finally, you will estimate the effort required for implementing machine learning features, enhancements, and bug fixes, collaborating with cross-functional teams to provide accurate and timely estimates.