Staff Data Scientist

About our group:Global Factory IT (GFIT) builds and operates mission-critical applications that power Seagate’s drive manufacturing operations worldwide. Our team delivers factory application development and integration services that support the end-to-end drive build process—from shop-floor execution, enterprise planning to AI /GenAI Solution—by modernizing and scaling Manufacturing Execution Systems (MES) and integrating them with ERP and other enterprise platforms. You will be part of a global, cross-site engineering team that partners closely with factory operations, process and industrial engineering, and corporate IT to deliver reliable, secure, and high-throughput AI and GenAI solutions.About the role – you will:We are seeking a Staff Data Scientist to lead the adoption of GenAI and machine learning across our manufacturing operations. In this role, you will architect and deliver scalable AI solutions that improve product quality, optimize production efficiency, and modernize engineering workflows through advanced analytics and GenAI-driven automation.About you: ·      AI Innovation: Lead ML/DL initiatives to improve manufacturing processes, increase yield, reduce scrap, enable predictive maintenance, and optimize production using complex tabular, image, and time-series data from machines and sensors.·      GenAI Strategy: Design, build, and scale Gen AI agents, RAG systems, and LLM applications to enhance engineering productivity, documentation, troubleshooting, and internal knowledge management.·      Engineering Excellence: Deploy production-grade AI systems using microservices architecture, robust CI/CD pipelines, and modern MLOps/LLMOps practices.·      Strategic Leadership: Partner with executives and cross-functional teams to define the long-term AI roadmap and translate technical capabilities into measurable business value.·      Mentorship& Culture: Mentor junior data engineers and data scientists, elevate team capabilities, and promote best practices in code quality, CI/CD, and responsible AI.Your experience includes:·      Education: Bachelor’s, Master’s, or PhD in Artificial Intelligence, Data Science, Computer Science, Engineering, or a related field.·      Technical Stack: Strong proficiency in Python, TensorFlow, PyTorch, AutoML frameworks, OpenAI APIs,LangChain, vector databases, and other modern AI frameworks.·      Production Deployment Experience: Hands-on experience with microservices architecture, CI/CD, Docker, Kubernetes, and MLOps/LLMOps in a production or industrial environment.·      Manufacturing Domain Expertise: Experience working with factory sensor data, machine logs, production line analytics, or predictive failure models.·      Leadership: Proven ability to lead technical projects, influence stakeholders, and communicate complex insights effectively to executive audiences.