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The role involves integration and validation of dynamic simulation models for HIL real-time closed loop simulation. Responsibilities include communication model design, troubleshooting bench issues, automating tasks with programming, and delivering effective HIL model rollouts while ensuring process efficiency.

The Senior Engineer - Throughput Simulation is responsible for developing and optimizing process models using simulation software, analyzing data for process improvements, leading simulation efforts across teams, and providing training to new engineers. They also track project progress and support performance objectives and strategies within the organization.

The Lead Engineer for Throughput Simulation will create discrete event simulation models for automotive plants, analyze and optimize processes, perform capacity assessments, and conduct scenario testing. The role requires leading simulation planning efforts, achieving excellence metrics, and supporting process improvements. They will also need to leverage their knowledge in various simulation and lean methodologies to enhance team capabilities and drive innovation.

The AI/ML Scientist Manager will lead the deployment of AI solutions, ensuring best practices in model operationalization. Responsibilities include framework development, collaborative implementation with Data Scientists, team leadership of ML engineers, managing ML operations with ML Flow, and overseeing CI/CD pipelines.

The role involves leading and mentoring a team of ML engineers, developing frameworks for AI model deployment, assuring code quality through CI/CD processes, and collaborating with various stakeholders to transition AI PoCs into production applications. A strong emphasis is placed on operationalizing AI models and maintaining best practices in machine learning operations.

The Staff Data Scientist will lead marketing analytics efforts, developing advanced models to optimize audience targeting and improve marketing strategies. They will work with diverse teams to implement data-driven solutions, analyze complex business problems, and enhance customer engagement through effective data storytelling.

The Senior Prognostics Data Engineer will design and deploy advanced signal processing methods for prognostics applications, lead failure mode analysis, analyze sensor data, develop health monitoring models, and optimize signal processing algorithms, collaborating with cross-functional teams and fostering continuous learning.